Civil Engineering RACE–II 6Th –7Th June, 2019

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2nd National Conference on Recent Advances in Civil Engineering RACE–II 6th –7th June, 2019

Department of Civil Engineering National Institute of Technology Patna Editors Ashok Rajpath, Patna – 800005 Email: [email protected] Prof. L.B. Roy Extn: +91-612-(2371715/2715/2371929/ Dr. S.K. Suman 2370419/2370843/2371930) * 126

Organized by Department of Civil Engineering National Institute of Technology Patna Ashok Rajpath, Patna – 800005 Bihar

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Printed by Excel Printing Universe, New Delhi–110 067 E-mail: [email protected] Preface

Department of Civil Engineering, National Institute of Technology Patna feels proud and privileged in successfully organizing the 2nd National Conference on Recent Advances in Civil Engineering (RACE) during 6-7 June 2019.It is indeed a great honor to organize the prestigious event RACE-II 2019 at the campus of NIT Patna, Patna, Bihar, India. The Civil Engineers need a continuous up-gradation of knowledge and experience in order to find the solution to the problems for serving the future generation on sustainable basis. The conference gave an opportunity to civil engineers to exchange their research and design methods so that quality infrastructural development is ensured in future. The RACE-II 2019 conference focused on the following themes: ●● New construction materials, equipment and technologies, ●● Design of high-rise buildings, ●● Economical and eco-friendly houses, ●● Geotechnical engineering, earthquake engineering and rock mechanics, ●● Transportation system engineering – new technologies, ●● Water resources development and management including Hydro-power engineering , ●● Geo-informatics, ●● Environmental issues i.e. EIA, Solid waste, water and waste-water management, ●● Disaster management, ●● Green buildings and ●● Bridge engineering. Research papers from all over country were received and published covering different themes in the proceedings. We had received 72 papers for this conference, after due peer review scrutiny 62 papers were selected for oral presentation. Out of 62 papers, 10 from Water Resources Engineering, 13 from Geotechnical Engineering, 07 from Environmental Engineering, 17 from Transportation Engineering and 15 from Structural Engineering were enlisted. The organizing committee is very much indebted to the authors of all technical papers which are included in the proceedings. We hope the contributions contained in the proceeding will be useful and refreshing source of information to all those technocrats who are working in these areas. This conference provide an excellent platform for interaction among experts from academia, research institution, industries, consultants, Government agencies and decision makers as the organizing committee had also invited several renowned personalities to deliver keynote/ invited lectures during the conference. We are very much thankful to our Patron, Prof. P.K. Jain, Director, NIT Patna for providing Institute facilities to organize this conference successfully. We extend our thanks to sponsors and co-sponsors including TEQIP III for supporting the conference. We express our sincere thanks to all the conference, sponsors, advertisers, authors and participants besides our Ph.D. and on M.Tech. scholars who have worked behind the scene and helped in organizing the conference successfully.

Prof. L.B. Roy Dr. S.K. Suman

[iii] Committees Patron Prof. Pradip Kumar Jain Director, NIT Patna

Convenors Prof. L.B. Roy Prof. Ramakar Jha Prof. Vivekanand Singh Professor & Dean (R&C) Professor & Head Professor Civil Engineering Civil Engineering Civil Engineering

Organising Secretaries Dr. S.K. Suman Dr. A.R. Quaff Dr. T. Roshni Assistant Professor Associate Professor Assistant Professor Civil Engineering Civil Engineering Civil Engineering

Organizing Committee

●● Prof. Ramakar Jha ●● Dr. Ajay Kumar ●● Prof. L.B. Roy ●● Dr. Sanjay Kumar ●● Prof. Vivekanand Singh ●● Dr. S.K. Suman ●● Prof. Ajay Kumar Sinha ●● Dr. Avijit Burman ●● Prof. S.S. Mishra ●● Dr. Bhupendra Singh ●● Prof. Sanjeev Sinha ●● Dr. Gyani Jail Singh ●● Prof. Manoj Kumar ●● Dr. Gopikrishnan T ●● Dr. N.S. Maurya ●● Dr. Ranja Bandyopadhyaya ●● Dr. A.R. Quaff ●● Dr. Reena Singh ●● Dr. Sunita Kumari ●● Dr. Roshni T ●● Dr. Baboo Rai ●● Dr. Lini Dev K ●● Dr. Anshuman Singh ●● Mr. S.K. Murmu ●● Dr. Pijush Samui ●● Dr. S.S. Chaudhary ●● Mr. S.K. Singh

[iv] Advisory Committee

Dr. I.N. Sinha Retd. Er.-in-Chief, WRD, Govt. of Bihar

Prof. T. Prasad Retd. Principal, BCE Patna

Dr. K.P. Singh Retd. Principal, BCE Patna

Dr. A.K. Sinha Retd. Principal, BCE Patna

Dr. S.K. Sinha Retd. Prof., NIT Patna

Dr. S.K. Sinha Prof. and Head, Civil Engg. Dept., BIT Patna

Dr. A.K. Lohani Scientist G, NIH Roorkee

Prof. (Dr.) V. Kumar Civil Engg. Dept., IIT-BHU

Dr. A. Upadhyaya Head, Water Management Div., ICAR Eastern Region

Dr. B. Manna Asst. Prof., Civil Engg. IIT Delhi

Dr. (Mrs.) T. Chakrabarthy Asst. Prof., Civil Engg, IIT Delhi

Dr. M.D. Singh Chief Engineer, Water Resource Dept., Govt. of Bihar

Dr. I.C. Thakur Chief Engineer, Water Resource Dept., Govt. of Bihar

Rabindra K. Shanker Chief Engineer, Water Resource Dept., Govt. of Bihar

[v] Details of Sub-committees

Registration Sub-committee Internet/ Press/ Media Sub-committee Dr. S.K. Suman Dr. Sanjay Kumar Dr. Anjali Sharma Dr. S. K. Suman Shalini Tiwari (Research Scholar) Dr. J.P. Singh Gautam Prakash (Research Scholar) Abhinav Prakash Singh (PG student) Vijeta Bachan (PG student) Rahul Ray (PG student)

Venue Sub-committee Cultural Event Sub-committee Prof. Vivekanand Singh Prof. Ramakar Jha Dr. Baboo Rai Prof. Vivekanand Singh Dr. Anjali Sharma Dr. Sanjay Kumar Rajnish Kumar (Research Scholar) Shalini Tiwari (Research Scholar) Shubham Singh (PG student) Vijeta Bachan (PG student) Ravi Ganga (PG student)

Purchase Sub-committee Site Visit Sub-committee Prof. Vivekanand Singh Dr. N.S. Maurya Dr. A.R. Quaff Dr. Baboo Rai Dr. S.K. Suman Dr. S.K. Suman Mr. Pankaj Kumar, Asst. Registrar (R & C) Animesh Pandey (PG student) Ravi Ganga (PG student)

Logistics Sub-committee Transport Sub-committee Dr. N.S. Maurya Prof. S.S. Mishra Dr. Anshuman Singh Dr. Bhupendra Singh Dr. Sanjay Kumar Dr. Ranja Bandyopadhyaya Dr. Reena Singh Dr. Gyani Jail Singh Saurav Shekhar Kar (Research Scholar) K. Praveen (Research Scholar) Avinash Kumar (PG student) Animesh Pandey (PG student) Bidyut Das (PG student) Saif Ali Akhtar (PG student) Pawan Kumar (PG student)

[vi] Keynote Invited Speakers

SESSION-I Prof. Santosh Kumar Retd. Professor of Civil Engineering, NIT Patna Prof. Vijay Labhsetwar Retd. Professor of IWM and Consultant, ICID

SESSION-II Prof. U.K. Singh Professor, Dept. of Mining Engineering, IIT (ISM) Dhanbad Prof. Nirmal Kumar Principal, Gaya College of Engineering, Gaya

SESSION-III Dr. (Mrs.) Bushra Zaman Consultant (Academics), SPIU, Science & Tech Dept., GoB Dr. N.S. Maurya Assoc. Prof., Civil Engineering, NIT Patna

SESSION-IV Prof. N.R. Patra Professor of Civil Engineering, IIT Kanpur Prof. Sanjeev Sinha Professor of Civil Engineering, NIT Patna

SESSION-V Er. Dukhi Sah Chief Technical Advisor, Police Building Construction Corporation, GoB Prof. S. Mandal Civil Engineering Dept., Jadavpur University, West Bengal

[vii] Programme Schedule

DAY–I (6th June 2019)

Time Event(s) 08:30 A.M. – 10:00 A.M. Registration 10:00 A.M. – 10:05 A.M. Lighting of Lamp 10:05 A.M. – 10:10 A.M. Saraswati Vandana 10:10 A.M. – 10:20 A.M. Welcome Address by Convenor 10:20 A.M. – 10:25 A.M. Address by the HOD (Civil) 10:25 A.M. – 10:35 A.M. Address by the Guest of Honour 10:35 A.M. – 10:45 A.M. Address by the Guest of Honour 10:45 A.M. – 11:00 A.M. Address by the Chief Guest 11:35 A.M. – 11:05 A.M. Vote of Thanks 11:05 A.M. – 11:35 A.M. High Tea 11:35 A.M. – 02:00 P.M. Technical Session I – Water Resources Engineering 02:00 P.M. – 03:00 P.M. Lunch Break 03:00 P.M. – 05:00 P.M. Technical Session II – Geotechnical Engineering 05:00 P.M. – 05:15 P.M. Tea 05:15 P.M. – 06:35 P.M. Technical Session III – Environmental Engineering 07:00 P.M. – 09:00 P.M. Dinner

DAY–II (7th June 2019)

Time Event(s) 09:00 A.M. – 10:30 A.M. Technical Session IV – Transportation Engineering 10:30 A.M. – 11:00 A.M. Tea 11:00 A.M. – 12:30 P.M. Technical Session V – Structural Engineering 12:30 P.M. – 01:30 P.M. Lunch Break 01:30 P.M. – 03:30 P.M. Panel Discussion 03:30 P.M. – 04:30 P.M. Valedictory Session 04:30 P.M. – 05:00 P.M. High Tea

[viii] Contents

 Preface iii  Committees v  Programme Schedule viii

1. Application of Minimax Probability Machine Regression in River Stage Forecasting Thendiyath Roshni, Madan K. Jha, Pijush Samui and Suraj Kumar 1 2. Water Quality Index of the Ganga River between Kali Ghat and Loharwa Ghat in Patna V.P. Dheeraj and A.R. Quaff 5 3. Fly Ash Bricks: Pressure Effect Arpan Singh, Abhishek Kumar and Syed Tabin Rushad 14 4. Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review Saurabh Kumar and A.R. Quaff 18 5. Determination of Liquefaction Potential of Sand-Fly Ash Blends Deepak Kumar and Siddhartha Sengupta 30 6. Annual Average Rainfall Distributions in Bihar Vikram Kumar 37 7. Concrete with Hybrid Polypropylene-Nylon Fibers Mani Mohan, Anurag and Sagar Sarangi 42 8. Measurement of Construction Productivity by using Situational Based Modelling Prasanna Honkalas and Vikas Varekar 50 9. Performance Characteristics of Ceramic Waste Concrete with Fly Ash and Granite Powder as Filler Nikhil Gharat and Vikas Varekar 59 10. Application of GIS into Pavement Management System Rohan Prakash and S.K. Suman 64 11. Investigation and Analysis of Scour Downstream of a Partial Submerged Vertical Weir Vishal Singh Rawat, Roshni Thendiyath, Sudhanshu Raj, Sandeep Kumar and Gaddam Vinay Kumar 72 12. Multi-Criteria Evaluation in GIS for Reconnaissance Survey of Route Selection in Difficult Terrain using Open Source Data and Software Bhupendra Singh and Sumedh Mhaske 77

[ix] Contents 13. Superpave Mix Design for DBM in Indian Scenario Digvijay Singh Chauhan and Sumedh Mhaske 88 14. Development of Sustainable Building Blocks using Fly Ash Blended with Different Additives: A Critical Review Bibhakar Kumar Singh and Siddhartha Sengupta 95 15. A Sustainable Approach to Subgrade Stabilization using Coir Fiber: Performance and Cost Evaluation Shaikh Arshad and Sumedh Mhaske 106 16. Suitability of EPS Geofoam in Construction of Road Embankment: Cost and Benefit Analysis Sarvesh Poredi and Sumedh Mhaske 112 17. Integrated Water Resources Management in Kosi Basin Rajesh Gupta 122 18. Laboratory Analysis of Bagasse Ash and Coir Fiber Composite Concrete Blocks for Low Cost Housing Abhishek Arvind Bane and Sumedh Mhaske 134 19. Laboratory Investigation of Charcoal Coconut Shell Ash Modified Bitumen Abhishek Dnyaneshwar Mahajan and Sumedh Mhaske 140 20. Determination of Mixing and Compaction Temperatures of Asphalt Binders Modified with EPDM Rubber Waste Ankush Kumar, Rajan Choudhary and Abhinay Kumar 147 21. Behaviour of Black Cotton Soil and Remedial Measures Sunita Kumari and Amrendra Kumar 156 22. Performance Analysis of At-grade and Grade Separated Intersection using Microscopic Simulation Atul Soni, Deepak Varshney, Anand Prabhat Verma and Nakul Gupta 161 23. Seepage Analysis of Railway Earthen Embankment in Mokama using RFEM to Study the Effect of Varying Hydraulic Conductivity V.K. Singh and A. Burman 166 24. Estimating Peak Ground Acceleration from Deterministic Seismic Hazard Analysis for Supaul District Near Bihar: Nepal Region R. Gautam, S. Kumar and A. Burman 174 25. Experimental Investigation of Batter Piles in Stratified Soil Deepak Varshney, Atul Soni, Anand Prabhat Verma and Nakul Gupta 182 26. Permeability Characteristics of Different Soils Added with Natural Fibres Nikhil Kumar Chaturvedi, U.K. Maheshwari and Alok Kumar Mishra 192 27. Relaibility of RSM towards Damage Identification in a Six-Storey Shear Building using Vibrational Parameters Anjneya Kumar and Koushik Roy 199

[x] Contents 28. Liquefaction Potential Evaluation and Design of Pile-foundation in Liquefiable Soils M.K. Paradhan, Shuvodeep Chakrabarty, G.R. Reddy and K. Srinivas 205 29. Effect of Sorption Phenomena in Groundwater Solute Transport Modeling Pappu Kumar and Anshuman Singh 216 30. Effect of Soaking Period of Soil on Liquid Limit and Plastic Limit Saurav Shekhar Kar, Suraj Kumar, Anurag Singh and L.B. Roy 220 31. Performance Evaluation of Reclaimed Asphalt Pavement (RAP) as Aggregates when Used with Waste Cooking Oil as a Rejuvenator in Bituminous Pavements Durgesh Sonawane and Pravin Chaudhari 227 32. Irrigation Water Productivity in Wan Command Area in Maharashtra, India: A Case Study Aman Tiwari, Abhinav Prakash, Ashutosh Upadhayaya and L.B. Roy 236 33. A Review on Factors Affecting Strength of Stone Columns in Soft Soil Shivangi Saxena and L.B. Roy 242 34. Numerical Study on the Dynamic Behaviour of Retaining Wall Backfilled with Waste Tyre Vikash Singh, Brijesh Kumar Sonkar, Vashi Ahmad and Agwe Michael Tobby 249 35. Effect of Commercial Traffic Overloading on Pavement Performance Gautam Prakash and S.K. Suman 256 36. Removal of Mercury from Aqueous Solution using Pine and Cinchona Bark Komal Rajpoot and S.K. Patidar 266 37. Early Contractor Involvement (ECI) as a Construction Project Delivery Method: An Overview Siddhesh D. Sagvekar and A.S. Wayal 275 38. An Eco-friendly Approach to Municipal Solid Waste Management in Indian Cities Smita Burrewar and Anjali Sharma 282 39. Resolving Water Scarcity in Bengaluru: An Innovative and Eco-friendly Approach Kanvi Tiwary and Anjali Sharma 283 40. Sustainable Urban Forms: A Critical Review of Vastushastra Naveen Nishant, Anjali Sharma, Bijay Kumar Das and Fulena Rajak 284 41. Rejuvenation and Redevelopment of Bellandur Lake Region of Bengaluru Kanvi Tiwary, Anjali Sharma and Ravish Kumar 295 42. Retrofitting for Daylighting of Existing Education Buildings: An Approach towards Sustainable Architecture Alok Kumar Maurya, Anjali Sharma, Ravish Kumar and Ajay Kumar 296

[xi] Contents 43. Analysis and Design of Stone Column using Different Techniques Shubham Singh and L.B. Roy 302 44. Study of Land Use Change on Soil Erosion in Sone Command Area using Remote Sensing and GIS Techniques K. Praveen, Animesh Pandey and L.B. Roy 308 45. Pond Ash Mixing Effect on the Properties of Soil to be Used for Subgrade Construction Diksha Singh, U.K. Maheshwari and N.K. Saxena 314 46. Sponge City: A New Concept in Urban Planning Santosh Kumar 321 47. Modelling the Pavement Condition Assessment using Fuzzy Inference System Madhavendra Sharma and S.K. Suman 325 48. Evaluation of Cement Treated Cmsdbc with Rapid Setting Bitumen Emulsion Rajnikant Verma and S.K. Suman 332 49. Relationship between Roughness and Pavement Distresses using ANN and Statistical Model Rajnish Kumar and S.K. Suman 339 50. Effect of Temperature Variation on Rutting and Fatigue Life of Flexible Pavement Vishal Kumar Narnoli and S.K. Suman 351 51. Barriers to Accessibility of Persons with Disabilities in Urban Public Transportation System Case Study of Bhopal, Madhya Pradesh, India Amit Kumar Bala and Ajay Kumar 356 52. Study of Drought and its Analysis in the Sone Command Area Gaurav Kumar and L.B. Roy 366 53. Structural Design of Safe Building Skin in Seismic Area Dukhi Sah 373 54. Estimation of Manning’s Roughness Coefficient at Baharwa Ghat of River Ganga, Patna Shashi Ranjan, Vivekanand Singh, Manish Kumar Ranjan and Anshu Raj 374 55. Comparative Study of Normal Clay Bricks, Fly Ash Bricks and Papercrete Bricks Supriya Kumari, Ajay Kumar and Ravish Kumar 380 56. Rock Support Interaction Analysis and Design of Support Upendra K. Singh 392 57. Unmanned Aerial Vehicles and Artificial Intelligence Tools for Wetland Monitoring Bushra Zaman 401

[xii] Contents 58. Changing Nature of Disaster Risk in the 21st Century: Evolving Role of Engineers in Disaster Management Paras Nath Rai 402 59. Elements of Comprehensive Mobility Plan for Patna 2018 Sanjeev Sinha 406 60. Mechanical Properties of Fibre Reinforced Self Compacting Concrete Brajkishor Prasad, Amit Patel and Prince Singh 407 61. Mechanical Behavior of Polymer Concrete and Ordinary Cement Concrete Exposed to Elevated Temperatures: A Comparative Study Brajkishor Prasad, S. Ganesan and Prince Singh 415 62. Cu(II) and Pb(II) Uptake by Granular Activated Alumina Columns Exposed to Mono– and Binary–Metal Ion Systems under a Fixed Concentration Gradient Manoj Kumar Yadav and Mohammad Jawed 425

AUTHOR INDEX 435

[xiii]

Application of Minimax Probability Machine Regression in River Stage Forecasting

Thendiyath Roshni1, Madan K. Jha2, Pijush Samui3 and Suraj Kumar4 1Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, India 2Professor, AgFE Department, Indian Institute of Technology Kharagpur, India 3Associate Professor, Department of Civil Engineering, National Institute of Technology Patna, India 4Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, India E-mail: [email protected], [email protected]

ABSTRACT This study emphasizes the comparison of two regression models for forecasting river stage and investigating the accuracies of the models selected. The models selected are Minimax Probability Machine Regression (MPMR) model and Support Vector Regression (SVR) Model. The efficacy of the models is tested with the data obtained from Kochi Prefecture, Japan. The forecasting performances of MPMR and SVR models are measured with the evaluation indices like RMSE, MAE and CC. Based on the indices and the visual comparison, the MPMR model produces better performance than SVR model. The results indicate that river stage forecasting with MPMR model can be used as an effective model for forecasting river stage. Keywords: River Stage Forecasting, MPMR, SVR

1. INTRODUCTION The reliable forecasting of any parameter affects the planning and operation, policy making and smooth functioning of any sector. For reservoir operation and water distribution to different sectors, accurate level of river stage is essential and reliable forecasting is required for the smooth operation and functioning of the system. The application of any models is critically dependent on the quality of their outputs. Therefore, model calibration and validation are required to improve their fidelity to actual conditions in any field of research. As a result, many approaches have applied for forecasting in the field of water resources engineering. All these approaches do not always produce forecasts with sufficient accuracy. Among these approaches, owing to huge data requirement, conventional models are ruled out by regression models [6]. For instance, several literatures have already proved the application of artificial neural network in forecasting many hydrological parameters [3,1]. Use of many machine learning tools have also enhanced in several fields of engineering during last few years [6]. Unfortunately, any models as such are not adequate for making predictions due to dynamical behavior of the hydrological system. Instead, a regression model by maximizing the minimum probability of future predictions within some bound of regression function is a novel and important tool to perform forecasting. This would be effective in achieving accurate results in a faster pace. Such a regression framework is Minimax Probability Machine Regression (MPMR) [7]. Few literatures of MPMR have already been discussed in different fields of engineering [2], image retrieval [9] etc. A recent work by [4] to forecast evaporative loss by LSSVR and its performance is evaluated and compared by GP and MPMR. The new approach in this paper is to widen the attempt to handle forecasting problems and to examine the applicability and capability of MPMR in in the field of water resources engineering. This work also aims at comparing the performances of MPMR with Support Vector Regression (SVR). Why SVR for comparison? It is because SVR is a familiar and effective data driven model and many research findings already proves its better performances than many conventional regression methods [5].

[1] paper id: 19003 Application of Minimax Probability Machine Regression in River Stage Forecasting Thendiyath Roshni1*, Madan K Jha1, Pijush Samui2, Kumar Suraj3

1*, 2, 3Department of Civil Engineering, National Institute of Technology Patna, India. Email: [email protected]

1AgFE Department, Indian Institute of Technology Kharagpur, India. Email: [email protected]

Abstract

This study emphasizes the comparison of two regression models for forecasting river stage and investigating the accuracies of the models selected. The models selected are Minimax Probability Machine Regression (MPMR) model and Support Vector Regression (SVR) Model. The efficacy of the models is tested with the data obtained from Kochi Prefecture, Japan. The forecasting performances of MPMR and SVR models are measured with the evaluation indices like RMSE, MAE and CC. Based on the indices and the visual comparison, the MPMR model produces better performance than SVR model. The results indicate that river stage forecasting with MPMR model can be used as an effective model for forecasting river stage.

Keywords: River stage forecasting, MPMR, SVR 1 Introduction The reliable forecasting of any parameter affects the planning and operation, policy making and smooth functioning of any sector. For reservoir operation and water distribution to different sectors, accurate level of river stage is essential and reliable forecasting is required for the smooth operation and functioning of the system. The application of any models is critically dependent on the quality of their outputs. Therefore, model calibration and validation are required to improve their fidelity to actual conditions in any field of research. As a result, many approaches have applied for forecasting in the field of water resources engineering. All these approaches do not always produce forecasts with sufficient accuracy. Among these approaches, owing to huge data requirement, conventional models are ruled out by regression models [6]. For instance, several literatures have already proved the application of artificial neural network in forecasting many hydrological parameters [3,1]. Use of many machine learning tools have also enhanced in several fields of engineering during last few years [6]. Unfortunately, any models as such are not adequate for making predictions due to dynamical behavior of the hydrological system. Instead, a regression model by maximizing the minimum probability of future predictions within some bound of regression function is a novel and important tool to perform forecasting. This would be effective in achieving accurate results in a faster pace. Such a regression framework is Minimax Probability Machine Regression (MPMR) [7]. Few literatures of MPMR have already been discussed in different fields of engineering [2], image retrieval [9] etc. A recent work by [4] to forecast evaporative loss by LSSVR and its performance is evaluated and compared by GP and MPMR. The new approach in this paper is to widen the attempt to handle forecasting problems and to examine the applicability and capability of MPMR in in the field of water resources engineering. This work also aims at comparing the performances of MPMR with Support Vector Regression (SVR). Why SVR for comparison? It is e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) because SVR is a familiar and effective data driven model and many research findings already proves its better performances2. METHODOLOGY than many conventional regression methods [5].

2 Methodology2.1 Minimax Probability Machine Regression (MPMR) 2.1 MinimaxMinimax ProbabilityProbability Machine Machine Regression Regression (MPMR) (MPMR) is developed and introduced by [7]. As mentioned by Minimax[4], MPMR Probability is an Machineimprovised Regression form of (MPMR)Support Vectoris developed Machine and (SVM). introduced Many by literature[7]. As mentioned reviews of by MPMR [4], MPMRreveals is an its improvised effective application form of Support in prediction Vector Machine of seismic (SVM). ultrasonic Many attenuationliterature reviews [2], biased of MPMR MPM reveals for image its effective application in prediction of seismic ultrasonic attenuation [2], biased MPM for image retrieval [9], face recognitionretrieval by[9], MPM, face recognition prediction ofby fast MPM, fading prediction channel of by fast MPM, fading forecasting channel by evaporative MPM, forecasting loss [4] andevaporative a few moreloss studies [4] and in othera few fields more of studies engineering. in other fields of engineering. MPMRMPMR follows follows a regression a regression model model for y for in they in form the formof of = [ ( , ) + ] ± (1)(1) � ∑�� Where,푦 x and훽 퐾 y 푥denotes푥 푏 the inputs휀 and corresponding outputs, K(xi, x) is kernel function. The present work uses Radial Basis Function (RBF) as the kernel function. The other variables , b are outputs obtained by MPMR algorithm and ε shows the limits of error fluctuations. All the inputs are normalized in the range of Where,0 to x1. and The y proposeddenotes the MPMR inputs algorithm and corresponding is established outputs, in MATLAB K(xi, x) is 2010. kernel function.β The present work uses Radial Basis Function (RBF) as the kernel function. The other variables β, b are outputs obtained by MPMR algorithm and ε shows the limits of error fluctuations. All the inputs are normalized in the range of 0 to 1. The 2.2 Support Vector Regression (SVR) proposed MPMR algorithm is established in MATLAB 2010. Support Vector Machines (SVM) for regression problems were first developed by [8]. and is based on 2.2 Support Vector Regression (SVR) statistical learning theory. SVM can be used for both classification and regression. Since the introduction Supportof SVM Vector application Machines in (SVM)regression for regressionanalysis, there problems has been were afirst rapid developed rise in the by applicability[8]. and is based and oneffectiveness statistical learningof SVMs theory. in different SVM can fields be ofused engineering. for both classification The difference and between regression. Support Since Vector the introduction Machine Regression of SVM application in regression analysis, there has been a rapid rise in the applicability and effectiveness of SVMs in differentand conventional fields of engineering. regression The techniques difference are between SVM uses Support structural Vector risk Machine minimization Regression and andnot empiricalconventional risk regressionminimization techniques principle. are SVM Hence uses the structural results obtainedrisk mini mizationby SVMs and are notalso empirical interesting risk and minimization encouraging principle. [10]. In Hencethis thepaper, results SVM obtained regression by SVMs analysis are has also been interesting used to and predict encouraging the river [10] stage.. In Regression this paper, isSVM the problemregression of

analysisestimating has been a function used to basedpredict on the a river given stage. data Regressionset. Let {x iis, y thei} be problem the inputs of estimating and the corresponding a function based outputs on a givenin datathe training set. Let set{xi, andyi} be the the length inputs of and data the i correspondingvaries from 1 outputsto N. The in thefunction training for set SVR and analysisthe length follows of data the i variesfunction from 1 as: to N. The function for SVR analysis follows the function as: = [ . ( ) + ] (2)(2) WhereWhere푦 w 푤is w the휙 is푥 weightthe weight푏 vector, vector, b is theb is bias the and bias ϕ (x)and is the(x) non is the-linear non-linear mapping mapping function. function. Kernel function Kernel usedfunction for thisused is Gaussian for this functiois Gaussiann. function. 2.3 Study Area and Data Used ϕ The2.3 data setsStudy were A takenrea and from D theata Monobe Used River, which encloses a drainage area of 2200 Ha, which is located in the Kochi Prefecture of Japan. Major rainfall comes from June to September and the mean annual rainfall is foundThe as data 2600 sets mm. were Rainfall taken fromevents the are Monobe often distributedRiver, which throughout encloses athe drainage year. However, area of 2200 October Ha, throughwhich is Februarylocated is inusually the Kochi characterized Prefecture as aof dry Japan. period. Major Rainfall rainfall data comes of 7 years from (01 June Jan to 1999 September to 31 Decem and berthe 2004)mean wereannual obtained rainfall from is Gomenfound as meteorological 2600 mm. Rainfall station. events The dailyare often minimum distributed and maximumthroughout tem theperatures year. However, for the 1999October–2004 periodthrough were February also gathered is usually from characterized the Gomen station.as a dry The period. daily Rainfall river stage data data of 7of years the Monobe (01 Jan Riv 1999er at theto Fukabuchi31 December gauging 2004) station were (at obtained 3.8 km from from the Gomen river mouth) meteorological for the 1998 station.–2004 periodThe daily were minimumgathered from and the maximumKochi Work temperatures Office, the Ministry for the 1999–2004of Construction period [1]. were also gathered from the Gomen station. The daily river stage data of the Monobe River at the Fukabuchi gauging station (at 3.8 km from the river mouth) for the 1998–2004 period were gathered from the Kochi Work Office, the Ministry of Construction [1]. 2.4 Input Selection and Data Normalization Inputs selected for River stage, R(t) simulation were based on correlation analysis. Correlation analysis was 2.4 Input Selection and Data Normalization carried out by R software. Correlation coefficient greater than 0.5 is considered as potential inputs. Hence the potentialInputs inputs selected found for wereRiver R(t stage,-1), R(t R(t)-2), simulation R(t-3), P(t were-1) and based P(t- 2).on ‘t’correlation stands for analysis. the time Correlationseries data at analysis t time andwas P represents carried out the byprecipitation. R software. For Correlation MPMR and coefficient SVR, data greater were normalizedthan 0.5 is betweenconsidered 0 to as1. potential70% of the inputs. data wereHence used thefor potentialtraining andinputs remaining found were 30% R(t-1), of the R(t-2), data were R(t-3), used P(t-1) for andtesting P(t-2).. MPMR ‘t’ stands analysis for the was time done series in MATLAB 2010 and SVR analysis in MATLAB 2017. [2] 2.5 Performance Evaluation Parameters The resulting error parameters: Root Mean Square Error (RMSE), Correlation Coefficient (CC) and Mean Absolute Error (MAE) between the predicted and observed values were compared. The best model was selected based on the performance indices. Lower value of RMSE, higher value of CC nearing to 1, and lower value of MAE indicates a better model. 3 Results and Discussion Having considered different input parameters for river stage simulation, by correlation analysis only 5 potential inputs were selected. As mentioned before 70% and 30% data were used for training and testing for MPMR and SVR models. The results obtained were compared and model performances were analyzed. The performance parameters i.e., RMSE, CC and MAE are shown in Fig. 1 for two developed models. From Figure 1, it is observed that the best performance is obtained for MPMR analysis. A visual comparison plot of observed and the predicted river stage using two models are shown in Fig. 2 and an enlarged view in Figure 3 (from 400 to 600 days in testing period. By comparing the Fig. 2 and 3 results, a good statistical performance is observed with the MPMR model results. The two developed models show a good performance and is getting along with the observed values and this proves the efficacy and predictive capability of the models. Among the two developed models, MPMR is showing marginally better performance than SVR model. Application of Minimax Probability Machine Regression in River Stage Forecasting data at t time and P represents the precipitation. For MPMR and SVR, data were normalized between 0 to 1.70% of the data were used for training and remaining 30% of the data were used for testing. MPMR analysis was done in MATLAB 2010 and SVR analysis in MATLAB 2017.

2.5 Performance Evaluation Parameters The Resulting Error Parameters: Root Mean Square Error (RMSE), Correlation Coefficient (CC) and Mean Absolute Error (MAE) between the predicted and observed values were compared. The best model was selected based on the performance indices. Lower value of RMSE, higher value of CC nearing to 1, and lower value of MAE indicates a better model.

3. RESULTS AND DISCUSSION Having considered different input parameters for river stage simulation, by correlation analysis only 5 potential inputs were selected. As mentioned before 70% and 30% data were used for training and testing for MPMR and SVR models. The results obtained were compared and model performances were analyzed. The performance parameters i.e., RMSE, CC and MAE are shown in Fig. 1 for two developed models. From Figure 1, it is observed that the best performance is obtained for MPMR analysis. A visual comparison plot of observed and the predicted river stage using two models are shown in Fig. 2 and an enlarged view in Figure 3 (from 400 to 600 days in testing period. By comparing the Fig. 2 and 3 results, a good statistical performance is observed with the MPMR model results. The two developed models show a good performance and is getting along with the observed values and this proves the efficacy and predictive capability of the models. Among the two developed models, MPMR is showing marginally better performance than SVR model.

Fig. 1: Performance of Testing Dataset

4. CONCLUSIONS This study shows a comparison of the two developed models MPMR and SVR for the prediction of daily river stage. The potential inputs found by correlation study for prediction are (R(t-1), R(t-2), R(t-3), P(t-1) and P(t-2). The data used for finding the effectiveness of the models are taken from Kochi Prefecture, Japan. Daily data of precipitation and river stage were available from Jan 1999 to Dec 2004. The efficacy of the developed models are assessed by parameters like CC, RMSE and MAE. The performance indicators and the visual comparison shows the dominance nature of MPMR model over SVR model. It also shows the predictive capability of MPMR model over SVR.

[3] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 2: Comparison between Observed and Predicted MPMR and SVR Model Results for Testing Period

Fig. 3: Comparison between Observed and Predicted MPMR and SVR Model Results from 400 Days to 600 Days in the Testing Period

REFERENCES [1] Jha, M.K., Jha, Sahoo, S.: Efficacy of neural network and genetic algorithm techniques in simulating spatio-temporal fluctuations of groundwater.Hydrol. Process. 29 (5), 671–691 (2015). [2] Kumar., M., Mittal, M., Samui, P.: Performance assessment of genetic programming and minimax probability machine regression for prediction of seismic ultrasonic attenuation. Earthq. Sci. 26(2), 147-150 (2013). [3] Coulibaly,P., Anctil, F., Aravena, R., Bobee, B.: Artificial neural network modeling of water table fluctuations. Water Resour. 37, 885–896(2001). [4] Deo, R. C., Samui, P.: Forecasting Evaporative Loss by Least-Square Support-Vector Regression and Evaluation with Genetic Programming, Gaussian Process, and Minimax Probability Machine Regression: Case Study of Brisbane. J. Hydrol. Eng. 22(6), 1-15(2017). [5] Maity, R., Bhagwat, P.P., Bhatnagar, A.: Potential of support vector regression for preiction of monthly streamflow using endogenous property. Hydrol. Proc. 24, 917-923(2010). [6] S. Long, S., Sivapragasam, C.: Flood stage forecasting with support vector machines. J. Amer. Water Res. Assoc. 38(1), 173-186(2002). [7] Strohmann, T., Grudic, G.Z.: A formulation for minimax probability machine regression. Proc., Advances in Neural Information Processing System, MIT Press, Cambridge, MA. 769–776(2002). [8] Vapnik, V.N.: Statistical learning theory, 1998, Wiley, New York. [9] Peng, X., King, I.: A biased minimax probability machine-based scheme for relevnance feedback in image retrieval. Neuro Computing. 72, 2046-2051(2009). [10] Dibike, Y. B., Velickov, S., Slomatine, D., Abbott, M. B.: Model induction with support vector machines:introduction and applications. J. of Comp. in Civil Eng. 15(3), 208-216(2001).

[4] Water Quality Index of the Ganga River between Kali Ghat and Loharwa Ghat in Patna

V.P. Dheeraj1 and Dr. A.R. Quaff2 1M.Tech. Student, Department of Civil Engineering, National Institute of Technology, Patna, Bihar, India 2Associate Professor, Department of Civil Engineering, National Institute of Technology, Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT In this manuscript, Water Quality Index (WQI) was determined of Ganga River during the session of 2017-2018 in Patna (Bihar, India). For the determination of average yearly WQI of Ganga River, from Kali Ghat to Loharwa Ghat were selected. The five selected locations (Kali Ghat, Krishna Ghat, Gandhi Ghat, Gulbi Ghat & Loharwa Ghat) were stretched about 4.5 km in length. the water samples were collected from these selected locations and it was analysed for eleven physicochemical parameters that 2- are Sulphate (SO4 ), Temperature, Total Dissolved Solids (TDS), Dissolved Oxygen (DO), Biochemical - Oxygen Demand (BOD), Total Hardness, Nitrate (NO3 ), Alkalinity, Turbidity, pH and Electrical Conductivity (EC). The Water Quality Index of River Ganga at five selected locations was calculated using Weighted Arithmetic Water Quality Index Method (WAWQIM) and that WQI was found in the range of (181.14 to 208.28), when turbidity parameter was considered. These calculated values of WQI show poor water quality at Krishna Ghat, Gandhi Ghat, Gulbi Ghat and very poor water quality at Kali Ghat, Loharwa Ghat therefore it is required to treat Ganga water before using it. Keywords: Ganga River Water, Water Quality Index, Water Quality Standard, Physicochemical Parameters

1. INTRODUCTION Ganga River is longest river basin in India. It covers total length of about 2525 km before meeting into bay of Bengal Therefore it is extreme source of water there where it flows in India and nearly one-fourth of total geographical area of India covered by it. The entire covered area by the Ganga basin is of Uttarakhand, Uttar Pradesh, Bihar, Delhi and some part of Haryana, Punjab, Himachal Pradesh, and West Bengal. Bhagirathi is extreme source stream of Ganga. It originated from Gangotri Glacier at Gaumukh at an elevation of 12,770 feet (3,892 m) [1]. As per report of Central Pollution Control Board (CPCB), the capacity of Sewage treatment plants is about 70.9% of the total sewage generation 143 million litre per day (MLD) in Patna [2]. This estimated value indirectly affects the Ganga water basin in case of water pollution. The river has been the focus of national and international intervention and study for past several decades to identify and establishes causes and impact of anthropogenic activities on river water quality. Ganga river plain is the most densely populated region due to more available of water & fertile soil in the existing basin of Ganga river. Today, more than 29 cities, about 79 towns and around thousand villages belongs along the Ganga basin, nearly all of their sewage about 1.3 million litre per day (MLD) directly discharge into the Ganga river basin along with thousand animal carcasses mainly cattle [3]. Domestic as well as industrial wastewater contributes as a major polluting source, whereas surface runoff is seasonal phenomenon controlled by climate only [4]. According to [5] Cultural and religious tourism on the banks of the river Ganga also deteriorates the water quality of Ganga River. Therefore this study was being aimed to evaluate the quality of water of river Ganga at different selected location in Patna. Doing so it can be predicted that whether the Ganga water is safe or not for take in to the consideration.

2. APPLICATIONS OF WATER QUALITY INDEX

[5] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) This study was an effort to assess the water quality of Ganga River in Patna city, India. For this, only eleven physicochemical parameters (Total Hardness, Alkalinity, pH, Dissolved Oxygen (DO), Biochemical - 2- Oxygen Demand (BOD), Turbidity, Electrical Conductivity (EC), Nitrate (NO3 ), Sulphate (SO4 ), Total dissolved Solid (TDS) and Temperature) have been selected. The suitability for human consumption the water quality parameters are studied. [6,7] have considered for standard values for various parameters.

3. MATERIAL AND METHOD This study was an attempt for evaluating the water quality of River Ganga in Patna. The sample were analysed as per standard method for eleven physicochemical parameters namely Total Hardness, - 2- Alkalinity, pH, DO, BOD, Turbidity, EC, Nitrate (NO3 ), Sulphate (SO4 ), Temperature and TDS. These given parameters have been analysed as per [8].

3.1 Selection of Location There was five locations at Ganga River were selected for the sampling namely Kali Ghat, Krishna Ghat, Gandhi Ghat, Gulbi Ghat and Loharwa Ghat respectively as shown into the Fig. 1 (Satellite view). The study area (Ganga River Patna) was located in Patna between longitude 85˚10’6.09”E to 85˚11’50.40”E and in between latitude 25˚37’19.77”N to 25˚36’58.21”N. The selected location was stretched around 4.5 km in length along the river.

Fig. 1: Satellite View of the Selected Location in Patna

3.2 Coordinate of Selected Location The coordinates of selected locations were found out with Google map and tabulated in Table 1.

Table 1: Coordinates of Selected Location

[6] Water Quality Index of the Ganga River between Kali Ghat and Loharwa Ghat in Patna

Locations Latitude Longitude Krishna Ghat 25˚37’19.77N 85˚10’6.09E Kali Ghat 25˚37’20.21N 85˚9’52.14E Gandhi Ghat 25˚37’19.76N 85˚10’20.64E Gulbi Ghat 25˚37’14.19N 85˚10’49.52E Loharwa Ghat 25˚36’58.21N 85˚11’50.40E

3.3 Sampling of Water at Selected Location The Water samples were collected about 0.5 metres below the water surface from each selected location of Ganga River. The water sample were collected monthly and finally averaged for yearly, as a yearly in session (2017-2018). Water samples were collected in polyethylene bottle of 5 litre capacity with properly

stopper. Every bottle was washed with 15% of HNO3 and then rinsed with distilled water for cleaning [9]. And finally the bottles were then preserved in a clean and dry place and each container was clearly marked with the name and date of sampling. 4. Analytical Method 4. Analytical Method For this study eleven physicochemical4. ANALYTICALparameters were takenMETHOD for the calculation of water Forquality this indexstudy (WQI) eleven of physicochemical Ganga water.For Five parametersthis parameters study eleven were were takenphysicochemical analysed for the instant calculation parameters at the sitesof water were(pH, taken for the calculation of water quality index qualityTotal Dissolved index (WQI) Solid of (TDS Ganga), Temperature,water.(WQI) Five parametersof Electrical Ganga water. wereConductivity Fiveanalysed parameters (EC)instant & were atTurbidity) the analysed sites. (RestpH, instant at the sites (pH, Total Dissolved Solid (TDS), Total Dissolved Solid (TDS), Temperature,- Electrical2- Conductivity (EC) & Turbidity). Rest - of the parameters (Nitrate (NO3 ), Temperature,Sulphate (SO 4Electrical), Alkalinity, Conductivity Total Hardness, (EC) & Turbidity).Dissolved Rest of the parameters (Nitrate (NO3 ), Sulphate - 2- of the parameters (Nitrate (NO3 ), Sulphate2- (SO4 ), Alkalinity, Total Hardness, Dissolved Solid (DO) and Biochemical Oxygen(SO Demand4 ), Alkalinity, (BOD)) Totalwere Hardness,performed Dissolvedin the laboratory. Solid (DO) The and Biochemical Oxygen Demand (BOD)) were SolidpH was (DO) analysed and Biochemical using pH meter Oxygen havingperformed Demand (Model (BOD)) in 140A). the laboratory. were The performed Alkalinity, The pH in Total thewas laboratory. Hardnessanalysed wereusingThe pH meter having (Model 140A). The Alkalinity, pHmeasured was analysed by Titration using pHas permeter Standard havingTotal (Modelmethod Hardness 140A).[8] were and The measuredDissolved Alkalinity, byOxygen Titration Total andHardness as BOD per Standardwerewere method [8] and Dissolved Oxygen and BOD - 2- were analysed- by Winkler’s method.2- Nitrate (NO ) & Sulphate (SO ) were analysed by using UV VIS measuredanalysed bbyy Winkler’sTitration asmethod. per Standard Nitrate method(NO3 ) &[8] Sulphate and Dissolved (SO4 ) Oxygenwere analysed and BOD by3 usingwere 4 Spectrophotometer- (Model evolution2- 201). Turbidity was analysed using Turbidity Rod. Total Dissolved analysedUV VIS bSpectrophotometery Winkler’s method. (Model Nitrate evolution (NO3 ) 201).& Sulphate Turbidity (SO was4 ) awerenalysed analysed using Turbidityby using Solid (TDS), temperature and electrical conductivity (EC) have been analysed by conductivity meter UVRod. VIS Total Spectrophotometer Dissolved Solid (Model(TDS), evolutiontemperature 201). and Turbidity electrical wasconductivity analysed (usingEC) haveTurbidity been (Co11_ Eutech model no. ECBO11001K). Rod.analysed Total by Dissolved conductivity Solid meter (TDS), (Co11_ temperature Eutech model and electricalno. ECBO11001K). conductivity (EC) have been analysed by conductivity meter (Co11_ Eutech model no. ECBO11001K). 5. Water quality index and its determinations5. WATER QUALITY INDEX AND ITS DETERMINATIONS 5. Water quality index and its determinations A water quality index provides a singleA water number quality that index expresses provides overall a single water number quality that at expresses a overall water quality at a certain location Acertain water location quality andindex time provides based on a severalsingleand time waternumber based quality that on expressesparameters.several water overall quality water parameters. quality at a certainAccording location to [ and10], timeto calculate based on WQIseveralAccording, total water eleven to quality [10], parameters parameters.to calculate were WQI, considered total eleven and parameters each were considered and each parameter was

Accordingparameter wasto [ 10assigned], to calculate with a definite WQIassigned, totalweightage witheleven a (W definiteparametersa) which weightage is were listed considered(W in aTable.2.) which and isRelative listed each in Table.2. Relative weights (Wr) were calculated as followed: parameterweights (W wasr) were assigned calculated with asa definitefollowed weightage (Wa) which is listed in Table.2. Relative weights (Wr) were calculated as followed = ÷ � = ÷ � 푊� 푊�� 푊푎푖 n = Number of parameters considered� for the�� WQI,�� Wr = Relative weight, 푊n = Number푊 � of 푊푎푖parameters considered for the WQI, Wr = Relative weight, nW =ai Number = assigned of parameters weight of considered each parameter. for the WQI,The�� calculatedWr = Relative relative weight, weight (Wr) for each W = assigned weight of each parameter. The calculated relative weight (W ) for each parameter is given Wparameterai = assigned is given weight in the ofTable each 2. parameter.ai The calculated relative weight (Wr) for each r in the Table 2. parameterThe quality is givenrating in scale the Table (Q) was2. measured for each parameter by dividing its respective Thestandard quality values rating as suggestedscale (Q) bywas BIS measured The& WHO quality forguidelines. rating each scaleparameter As following(Q) was by measureddividing its for respective each parameter by dividing its respective standard values standard values as suggested by BIS as & WHOsuggested= [ guidelines.÷ by] ×BIS100 As& WHOfollowing guidelines. As following: Quality rating scale Q for the DO and =pH[ is ÷having] × different100 methods. The ideal values of 푄� 퐶� 푆� Qualityboth parameters rating scale (V i)Q offor pH= the DO(7.0) and and pH for is DO= having (14.6) different were methods.deducted Thefrom ideal the valuesmeasured[7 ] of 푄� 퐶� 푆� bothvalues parameters in the samples. (Vi) ofAs pH= following (7.0) and for DO= (14.6) were deducted from the measured values in the samples. As following pH; DO = [( ) ÷ ( )] × 100 pH; DO = [( ) ÷ ( )] × 100 Qi = quality rating scale, Ci = measured concentration of each parameter, 푄� 퐶� − 푉� 푆� − 푉� QSii ==drinking quality rating water scale, standard Ci = values measured for each conc parameterentration of according each parameter, to BIS & WHO guidelines. 푄� 퐶� − 푉� 푆� − 푉� SiThe =drinking next is sub water-indices standard (SI) valueswas calculated for each asparameter followed according to BIS & WHO guidelines. The next is sub-indices (SI) was calculated =as followed× . Water quality index (WQI) was calculated =as followed× . 푆퐼� 푊� 푄� Water quality index (WQI) was calculated as followed= . 푆퐼� 푊� 푄� The computed WQI values were classified according= . [11,12]. 푊푄퐼 Ʃ푆퐼� The computed WQI values were classified according� [11,12]. 푊푄퐼 Ʃ푆퐼

4. Analytical Method 4. Analytical Method 4. Analytical MethodFor this study eleven physicochemical parameters were taken for the calculation of water For this study qualityeleven indexphysicochemical (WQI) of Ganga parameters water. wereFive parameterstaken for the were calculation analysed instantof water at the sites (pH, Forquality this indexstudy (WQI)elevenTotal Dissolved ofphysicochemical Ganga water.Solid (TDS Five parameters ),parameters Temperature, were were taken Electrical analysed for the Conductivityinstant calculation at the (EC)sitesof water (&pH, Turbidity) . Rest - 2- qualityTotal Dissolvedindex (WQI)of Solidthe of parameters (TDSGanga), water.Temperature, (Nit Fiverate parameters(NO Electrical3 ), Sulphate were Conductivity analysed(SO4 ), (EC)instantAlkalinity, & at Turbidity) the Total sites Hardness, .( pH,Rest Dissolved Total DissolvedSolid Solid (DO) (TDS and), Temperature, Biochemical- OxygenElectrical2- Demand Conductivity (BOD)) (EC) were & performed Turbidity) in. Rest the laboratory. The of the parameters (Nitrate (NO3 ), Sulphate (SO4 ), Alkalinity, Total Hardness, Dissolved - 2- ofSolid the (DO)parameters andpH Biochemical (Nitwasrate analysed (NO Oxygen3 using), Sulphate DemandpH meter (SO (BOD)) having4 ), Alkalinity, were(Model performed 140A). Total TheHardness,in the Alkalinity, laboratory. Dissolved Total The Hardness were SolidpH was (DO) analysed and measuredBiochemical using pH by meter OxygenTitration having Demand as (Modelper Standard(BOD)) 140A). were method The performed Alkalinity, [8] and in Dissolved Totalthe laboratory. Hardness Oxygen Thewere and BOD were - 2- pHmeasured was analysed by Titrationanalysed using pH asby meter perWinkler’s Standard having method. (Modelmethod Nitrate140A). [8] and (NOThe Dissolved 3Alkalinity,) & Sulphate Oxygen Total (SO Hardnessand4 )BOD were were wereanalysed by using measured by TitrationUV VIS as Spectrophotometer per Standard method (Model- [8] evolutionand Dissolved 201).2- OxygenTurbidity and was BOD analysed were using Turbidity analysed by Winkler’s method. Nitrate (NO3 ) & Sulphate (SO4 ) were analysed by using - 2- analysedUV VIS bSpectrophotometery Winkler’sRod. Total method. Dissolved (Model Nitrate evolutionSolid (NO (TDS),3 ) 201).& Sulphate temperature Turbidity (SO was4and) wereaelectricalnalysed analysed usingconductivity byTurbidity using ( EC ) have been UVRod. VIS Total Spectrophotometer Dissolvedanalysed Solid by conductivity (Model(TDS), evolutiontemperature meter (Co11_201). and Turbidity electricalEutech modelwas conductivity a nalysedno. ECBO11001K). using(EC) Turbidityhave been Rod. Total Dissolved Solid (TDS), temperature and electrical conductivity (EC) have been analysed by5. conductivity Water quality meter index (Co11_ and Eutech its determinations model no. ECBO11001K). analysed by conductivity meter (Co11_ Eutech model no. ECBO11001K). 5. Water qualityA index water and quality its determinations index provides a single number that expresses overall water quality at a 5. Water quality index and its determinations A water qualitycertain index location provides and a timesingle based number on several that expresseswater quality overall parameters. water quality at a Acertain water location qualityAccording andindex time provides basedto [10 on a], severalsingleto calculate numberwater qualityWQI that, totalexpressesparameters. eleven overall parameters water qualitywere considered at a and each certainAccording location to parameter[and10] ,time to calculatebased was assignedon severalWQI , with totalwater a eleven definitequality parameters parameters.weightage were(W a) consideredwhich is listed and ineach Table.2. Relative According to [weights10], to (Wcalculater) were WQI calculated, total aseleven followed parameters were considered and each parameter was assigned with a definite weightage (Wa) which is listed in Table.2. Relative parameter was assigned with a definite weightage (Wa) which is listed in Table.2. Relative weights (Wr) were calculated as followed = ÷ weights (Wr) were calculated as followed � = ÷ �푊� 푊 �� 푊푎푖 n = Number of parameters= considered÷ � for the WQI,�� Wr = Relative weight, � �� Wai = assigned weight푊 of 푊each parameter.� 푊푎푖 The calculated relative weight (Wr) for each n = Number of parameters considered� for the�� WQI,�� Wr = Relative weight, n = Number of parametersparameter is considered given in푊 the for Table the푊 WQI, 2. � W푊푎푖r = Relative weight, Wai = assigned weight of each parameter. The�� calculated relative weight (Wr) for each Wparameterai = assigned is givenThe weight inquality the of Table eachrating 2. parameter. scale (Q) Thewas calculatedmeasured forrelative each weightparameter (W rby) for dividing each its respective parameter is givenstandard in the valuesTable 2.as suggested by BIS & WHO guidelines. As following The quality rating scale (Q) was measured for each parameter bynd dividing its respective = [ e-Book:÷ ] 2× National100 Conference on Recent Advances in Civil Engineering (RACE-II) Thestandard quality values rating as suggestedscale (Q) bywas BIS measured & WHO for guidelines. each parameter As following by dividing its respective standard values as suggested by BIS & WHOQuality guidelines. rating scale As Qfollowing for the DO and pH is having different methods. The ideal values of both parameters Quality rating scale Q for= the[ DO÷ and] ×� 100pH is � having� different methods. The ideal values of (V= )[ of÷ pH=] ×푄 (7.0)100 퐶and 푆for DO= (14.6) were deducted from the measured values in the samples. As Quality rating bothscale parametersQ for the DO(Vi )and of pH=pHi is (7.0) having and different for DO= methods. (14.6) were The idealdeducted values from of the measured Quality rating scalevalues Q in for the the samples. DO and As푄 �following:pH following is퐶 �having푆 � different methods. The ideal values of both parameters (Vi) of pH= (7.0) and� for� DO=� (14.6) were deducted from the measured 푄 pH퐶 ; DO푆 = [( ) ÷ ( )] × 100 bothvalues parameters in the samples. (Vi) of As pH= following (7.0) and for DO= (14.6) were deducted from the measured values in the samples.Qi = quality As following rating scale, Ci = measured concentration of each parameter, pH; DO = 푄Q[(� = quality) ÷ (rating퐶� −scale,)푉]�× 100C 푆=� −measured푉� concentration of each parameter, Si =drinking pH water; DO standard = [( i values) ÷ for( each parameter)] × 100i according to BIS & WHO guidelines. Qi = quality rating scale, Ci = measured concentration of each parameter, 푄� Si퐶 =drinking� − 푉� water푆� − 푉 standard� values for each parameter according to BIS & WHO guidelines. QSii = =drinking quality rating waterThe scale, nextstandard isC� i sub= valuesmeasured-indices for (SI) eachconc� was entrationparameter� calculated of� according each as� followedparameter, to BIS & WHO guidelines. 푄 퐶 − 푉 푆 − 푉= × SiThe =drinking next is subwater-indices standard (SI) values was calculated for eachThe parameter asnext followed is sub-indices according (SI) to BIS was. & calculated WHO guidelines. as followed: The next is sub-Waterindices quality (SI) was index calculated (WQI) wasas followed calculated as followed = × . � � � = × 푆퐼 푊 푄 Water quality index (WQI) was calculated as followed. = . Water quality indexThe computed(WQI) was WQI calculated valuesWater푆퐼 � aswere followed 푊quality �classified푄� index according (WQI) was [11 calculated,12]. as followed: � =� � . � 푆퐼 푊= 푄 푊푄퐼 Ʃ푆퐼 The computed WQI values were classified according. [11,12]. The computed WQI values were classified푊푄퐼 accordingƩ푆퐼 �[11,12]. The computed� WQI values were classified according [11,12]. 푊푄퐼 Ʃ푆퐼

Table 2: Assign Weight & Relative Weight of Each Parameter

Parameters Assign Weight (Wa) Relative Weight (Wr) pH 4 0.102

TDS 4 0.102

DO 5 0.121

BOD 3 0.076

Alkalinity 2 0.051

Total Hardness 3 0.076

Turbidity 2.2 0.056

Nitrate 4 0.102

Sulfate 4 0.102

Temperature 3 0.076

EC 5 0.121

6. RESULTS AND DISCUSSIONS Water quality parameters namely Total Hardness, Alkalinity, pH, Dissolved Oxygen (DO), Biochemical - 2- Oxygen Demand (BOD), Turbidity, Electrical Conductivity (EC), Nitrate (NO3 ), Sulphate (SO4 ), Temperature and Total dissolved Solid (TDS) at five different location at Ganges River within a stretch of about 4.5 km at Patna city were measured. All values of each parameter obtained & compared with the guideline values as suggested above. Based on the data obtained from different locations, WQI were calculated and listed in the Table 3 to Table 7.

Table 3: WQI at Kali Ghat

[8] Water Quality Index of the Ganga River between Kali Ghat and Loharwa Ghat in Patna

Avg. Data Assign Standard Relative Quality Rating Sub-Indices Parameters (Ci) Weight (Wa) Value (Si) Weight (Wr) Scale (Qi) (SIi) pH 7.8 4 7.5 0.102 160 16.32 TDS 293 4 500 0.102 58.6 5.9772 DO 7.1 5 5 0.127 78.125 9.92188 BOD 5.9 3 5 0.076 118 8.968 Alkalinity 55 2 200 0.051 27.5 1.4025 Total Hardness 236.4 3 300 0.076 78.8 5.9888 Turbidity 112.3 2.2 5 0.056 2246 125.776 Nitrate 0.19 4 45 0.102 0.4222 0.04307 Sulphate 38.65 4 200 0.102 19.325 1.97115 Temperature 25.76 3 25 0.076 103.04 7.83104 EC 597 5 300 0.121 199 24.079 WQI 39.2 208.279

Table 4: WQI at Krishna Ghat Avg. Data Assign Standard Relative Quality Rating Sub-Indices Parameters (Ci) Weight (Wa) Value (Si) Weight (Wr) Scale (Qi) (SIi) pH 7.98 4 7.5 0.102 196 19.992 TDS 275.77 4 500 0.102 55.154 5.62571 DO 7 5 5 0.127 79.17 10.0546 BOD 7.2 3 5 0.076 144 10.944 Alkalinity 39.3 2 200 0.051 19.65 1.00215 Total Hardness 198.2 3 300 0.076 66.067 5.02107 Turbidity 97.77 2.2 5 0.056 1955.4 109.502 Nitrate 0.511 4 45 0.102 1.1356 0.11583 Sulphate 34.62 4 200 0.102 17.31 1.76562 Temperature 25.86 3 25 0.076 103.44 7.86144 EC 518.43 5 300 0.121 172.81 20.91 WQI 39.2 192.795

Table 5: WQI at Gandhi Ghat Avg. Data Assign Standard Relative Quality Rating Sub-Indices Parameters (Ci) Weight (Wa) Value (Si) Weight (Wr) Scale (Qi) (SIi) pH 7.79 4 7.5 0.102 158 16.116 TDS 228.5 4 500 0.102 45.7 4.6614 DO 7.4 5 5 0.127 75 9.525 BOD 5.8 3 5 0.076 116 8.816 Alkalinity 52.2 2 200 0.051 26.1 1.3311 Total Hardness 218.66 3 300 0.076 72.887 5.53939 Turbidity 108.77 2.2 5 0.056 2175.4 121.822 Nitrate 1.039 4 45 0.102 2.3089 0.23551 Sulphate 40.98 4 200 0.102 20.49 2.08998 Temperature 27.32 3 25 0.076 109.28 8.30528 EC 529.7 5 300 0.121 176.57 21.3646 WQI 39.2 199.807

Table 6: WQI at Gulbi Ghat

[9] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Avg. Data Assign Standard Relative Quality Rating Sub-Indices Parameters (Ci) Weight (Wa) Value (Si) Weight (Wr) Scale (Qi) (SIi)

pH 8.1 4 7.5 0.102 220 22.44

TDS 249.67 4 500 0.102 49.93 5.0933

DO 7.43 5 5 0.127 74.69 9.4856

BOD 7.03 3 5 0.076 140.6 10.686

Alkalinity 43.45 2 200 0.051 21.73 1.108

Total Hardness 197.76 3 300 0.076 65.92 5.0099

Turbidity 94.89 2.2 5 0.056 1898 106.28

Nitrate 0.176 4 45 0.102 0.391 0.0399

Sulphate 26.75 4 200 0.102 13.38 1.3643

Temperature 25.43 3 25 0.076 101.7 7.7307

EC 295.3 5 300 0.121 98.43 11.91

WQI 39.2 181.14

Table 7: WQI at Loharwa Ghat

Avg. Data Assign Standard Relative Quality Rating Sub-Indices Parameters (Ci) Weight (Wa) Value (Si) Weight (Wr) Scale (Qi) (SIi)

pH 8.01 4 7.5 0.102 202 20.604

TDS 224.57 4 500 0.102 44.91 4.5812

DO 7.01 5 5 0.127 79.06 10.041

BOD 7.47 3 5 0.076 149.4 11.354

Alkalinity 38.43 2 200 0.051 19.22 0.98

Total Hardness 202.2 3 300 0.076 67.4 5.1224

Turbidity 112.43 2.2 5 0.056 2249 125.92

Nitrate 0.285 4 45 0.102 0.633 0.0646

Sulphate 29.88 4 200 0.102 14.94 1.5239

Temperature 25.89 3 25 0.076 103.6 7.8706

EC 395.9 5 300 0.121 132 15.968

WQI 39.2 204.03 Graphical representation of each parameter’s concentration at all selected different locations respectively.

[10] Water Quality Index of the Ganga River between Kali Ghat and Loharwa Ghat in Patna Parameter concentration 700 398.9 600

500 Parameter concentration 700 400 600 224.57 300 500 202.2 200 400 112.43 398.9 100 38.43 300 29.88 25.89 8.01 7.01 7.47 0.285 0 200 224.57 202.2 100 112.43 8.01 7.01 7.47 38.43 0.285 29.88 25.89 0 LOCATIONS Kali Ghat Krishna Ghat Gandhi Ghat gulbi Ghat Loharwa Ghat

Fig. 2: Graphical Representation of Each Parameter’s Concentration at all Selected Different Locations

The WQI value at different locations is presented graphically and shown in Fig. 3. LOCATIONS Kali Ghat Krishna Ghat Gandhi Ghat gulbi Ghat Loharwa Ghat

215 210 208.28 204.03 205 199.81 200 195 192.8 190

185 181.14 180 175 170 165 Krishna Ghat Kali Ghat Gandhi Ghat Gulabi Ghat Loharwa Ghat

WQI Fig. 3: Graphical Representation of Average Yearly WQI at Different Location

[11] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) A comparison of water quality index based on scale as suggested by [11,12] is shown in Table 8.

Table 8: Water Quality Classification WQI Value [11] Water Quality WQI Value [12] <50 Excellent 0–25 50–100 Good Water 26–50 100–200 Poor Water 51–75 200–300 Very Poor Water 76–100 >300 Water Unsuitable For Use Above 100 All the values of Water Quality Index (WQI) were calculated and compared then concluded some specific results. The standard classification of water quality has shown in Table 9 below.

Table 9: Water Quality Index Scale at Different Locations Water Quality Scale Water Quality Scale Suggested Location WQI Suggested by [11] by [12] Krishna Ghat 192.8 Poor Water Unsuitable For Use Kali Ghat 208.28 Very Poor Water Unsuitable For Use Gandhi Ghat 199.81 Poor Water Unsuitable For Use Gulabi Ghat 181.14 Poor Water Unsuitable For Use Loharwa Ghat 204.03 Very Poor Water Unsuitable For Use

7. CONCLUSION In this study, the Water Quality index (WQI) was calculated average yearly at selected location and its value was fluctuating at every location i.e Ghat. The results represent mainly poor to very poor & unsuitable for use of water quality at each selected location according to different concepts. The analysis of water quality was done using WQI concepts. It was found a significant decline in water quality of Ganges River after analysis. The calculated average yearly WQI values from Krishna Ghat to Loharwa Ghat were recorded [181.14, 192.8, 199.81, 204.03, 208.28] at Gulbi Ghat, Krishna Ghat, Gandhi Ghat, Loharwa Ghat, Kali Ghat respectively which represents poor water quality according to Ramakrishnaiah but unsuitable for use according to A K Yadav at Gulbi Ghat, Krishna Ghat, Gandhi Ghat and very poor water quality according to Ramakrishnaiah and unsuitable for use according to Yadav at rest of the Ghat i.e. Loharwa Ghat, Kali Ghat respectively. The reasons behind (poor, very poor and unsuitable for use) quality of water of Ganga River in Patna are direct sewage disposal, animal bathing, cloth washing and high silt discharge therefore here results suggested that at least once treatment of Ganga water may be needed for consumption for different purposes like bathing, drinking and irrigation purposes.

ACKNOWLEDGMENT This research work was carried out in the Environmental Engineering Department and received financial support from National Institute of Technology Patna (NITP Dept. of Civil Engineering Patna), India is greatly appreciated and acknowledged.

[12] Water Quality Index of the Ganga River between Kali Ghat and Loharwa Ghat in Patna REFERENCES [1] Bhutiani, R. et al. 2016. “Assessment of Ganga River Ecosystem at Haridwar, Uttarakhand, India with Reference to Water Quality Indices.” Applied Water Science 6(2):107–13. [2] CPCB. 2013. “Pollution Assessment: River Ganga.” Central Pollution Control Board, Ministry of Environment and Forests, Govt. of India 1–206. [3] Bhardwaj, Vikram, Dhruv Sen Singh, and A. K. Singh. 2010. “Water Quality of the Chhoti Gandak River Using Principal Component Analysis, Ganga Plain, Water Quality of the Chhoti Gandak River Using Principal Component Analysis, Ganga Plain, India.” (July 2017):117–27. [4] Singh, Kunwar P., Amrita Malik, Dinesh Mohan, and Sarita Sinha. 2004. “Multivariate Statistical Techniques for the Evaluation of Spatial and Temporal Variations in Water Quality of Gomti River (India) - A Case Study.” Water Research 38(18):3980–92. [5] Farooquee, Nehal A., Tarun K. Budal, and R. K. Maikhuri. 2008. “Environmental and Socio-Cultural Impacts of River Rafting and Camping on Ganga in Uttarakhand Himalaya.” Current Science 94(5):587–94. [6] BIS. 2009. “Draft Indian Standard drinking water – specification ( Second Revision of IS 10500 ).” Water Supply 25(13):1–24. [7] Graham, Nigel. 1999. “Guidelines for Drinking-Water Quality, 2nd Edition, Addendum to Volume 1 – Recommendations, World Health Organisation, Geneva, 1998, 36 Pages.” Urban Water 1(2):183. [8] Clesceri, L. S., A. E. Greenbaerg, and A. D. Eaton. 1998. “Standard Methods for Examination of Water and Wastewater (Standard Methods for the Examination of Water and Wastewater).” American Public Health Association (APHA): Washington, DC, USA 552:5–16. [9] Sharma, Prerna, Prabodha Kumar Meher, Ajay Kumar, Yogendra Prakash Gautam, and Kaushala Prasad Mishra. 2014. “Changes in Water Quality Index of Ganges River at Different Locations in Allahabad.” Sustainability of Water Quality and Ecology. [10] Alobaidy, Abdul Hameed M. Jawad, Haider S. Abid, and Bahram K. Maulood. 2010. “Application of Water Quality Index for Assessment of Dokan Lake Ecosystem, Kurdistan Region, Iraq.” Journal of Water Resource and Protection 02(09): 792–98. [11] Ramakrishnaiah, C R Sadashivaiah, C Ranganna, G Rama 2009, Assessment of Water Quality Index for the Groundwater in Tumkur Taluk, Karnataka State, India India. E- Journal of Chemistry 6: 523-530, (2009) [12] A.K. Yadav, P. Khan, S.K. Sharma, Water quality index assessment of groundwater in Todaraisingh tehsil of Rajasthan State, India-A greener approach. E-Journal of Chemistry, 7:S428-S432, (2010).

[13] Fly Ash Bricks: Pressure Effect

Arpan Singh1, Abhishek Kr.2 and Syed Tabin Rushad3 1UG Student, BIT Mesra, Patna Centre, Patna, Bihar, India 2Lecturer, Government Polytechnic Nawada, Bihar, India 3Assistant Professor, BIT Mesra, Patna Centre, Patna, Bihar, India

ABSTRACT The quantum of fly ash requiring disposal is touching alarming limits. Although, a lot of investigations are still in progress for using the fly ash in concrete manufacturing and geotechnical engineering, the utilization of fly ash in brick manufacture is an excellent alternative for low cost housing. The aim of the present study is to investigate the strength and water absorption characteristic of bricks made using fly ash as one of the raw materials. The raw materials used were lime and fly ash. The results show that the hand moulded bricks develop least strength while pressure moulded bricks develop high strength for each type of specimen.The bricks satisfy the criterion of class 5, when lime and fly ash proportion is 40: 60 and pressure applied is 50 kN. Keywords: Lime, Fly Ash, Compressive Strength and Water Absorption

1. INTRODUCTION Fly ash is a by-product of the combustion of pulverized coal in industries like thermal power plants, fertilizer plants,etc. Fly ash produced may be up to 20% or even more of total coal burnt. This causes serious problems in its disposal and environmental pollution, in addition to occupying large tracts of scare cultivable land. The usual form of disposal of bottom and fly-ash is dumping in ponds. This waste material, available in large quantities near thermal power plants, can be utilized as main raw material in the manufacture of bricks beside cement, concrete manufacture and land filling. In their experiment, Sumathi et al. (1) observed that the optimized compressive strength of fly ash brick of size 230 x 110 x 90 was optimum with mix percentage of Flyash-15%, Lime-30%, Gypsum-2% & Quarry Dust-53%. Hwang lung et al. (2) concluded that at temperature of 350C, class-F fly ash(FA) & residual rice husk (RHA) have potential to produce ecofriendly bricks for construction. Nataatmadja (3) was found out in the experiment that it was possible to produce lightweight pressed bricks by varying proportions of fly ash, sand, hydrated lime, sodium silicate and water at a firing temperature of around 5500C and if proper proportioning was done, fly ash bricks have comparable compressive strength with typical value of common clay bricks. It was also observed that a combination of 70/30 for fly ash/common sand with 15% liquid sodium silicate and 5% lime would produce best performing bricks in terms of strength, mouldability and water absorption. Since 2003, Government of India had made it mandatory to use fly ash in brick manufacture within 100 Km radius of its production. For last several decades attempts are being made to find a suitable method for the disposal and proper utilization of fly ash. The construction industry can utilize this waste product in huge quantities. Its use in cement and concrete manufacture is promising. Another costlier building material which can utilize fly ash is bricks. The brick manufactured from 100% ash, however, has some disadvantages; although freeze-thaw resistant, the brick has porosity and is prone to chipping. Karthikeyan et al. (4) studied the utilization of fly ash in bricks. The fly ash can be effectively used for [14] Fly Ash Bricks: Pressure Effect manufacture of bricks using fly-ash, lime, sand and gypsum. The useful proportion found was 1:3.33:4:25 (Gypsum: Lime: Sand: Fly ash). Sharda et al. (5) found that 20–50% fly ash can be used in manufacture of fly ash clay brick. However, these bricks are more porous than the flyash bricks. In this paper, the results of experiments conducted (6) to find the suitability of fly ash as one of the raw materials for brick manufacture are presented. Further, the influence of pressure moulding on compressive strength and water absorption is also investigated.

2. MATERIALS The materials used in the present investigation are lime and fly ash. The materials were tested as per the relevant Indian Standards and results are presented below. Lime (L): The lime was tested as per the provisions of IS: 6932–1973. The impurities present in lime wereless than 5%. The Optimum Moisture Content (OMC) and Maximum Dry Density (MDD) were found to be 42.5% and 1080 kg/m3, respectively. Fly Ash (FA): The fly ash for the present investigation was procured from IFFCO, Phulpur, Allahabad. The specific gravity of fly ash was 2.08. In all the samples, fraction finer than 2µ was maintained as 7.7%. Its Liquid Limit (LL), Plastic Limit (PL), and Plasticity Index (PI)were 15%, 15%, and 0% respectively. The OMC and MDD were 45% and 800 kg/m3 respectively. The chemical composition of fly ash is presented in Table 1.

Table 1: Chemical Composition of Fly Ash

Chemical Unburnt SiO Al O Fe O TiO CaO K O MgO Mo O Composition Carbon 2 2 3 2 3 2 2 2

% by weight 12.00 57.77 23.92 9.56 1.63 2.24 0.60 1.28 0.13

The modular bricks samples of size 190 mm × 90 mm × 90 (IS: 12894-2002) were cast in lab using the L and FA in ratios of 20: 80, 30: 70, and 40: 60, respectively. The sample was mixed with sufficient quantity of water to obtain working consistency for moulding. The clean mould was filled with the lime and fly ash mixture without allowing any air bubble. The surplus mix was removed and top surface was leveled. For the hand moulded bricks no pressure was applied on the mould. The pressure moulded bricks were prepared by applying load of 10, 30 and 50 kN, respectively. The moulded brick were allowed to dry for two days protecting from direct sun. The specimens were immersed in water at room temperature for 24 hours and thereafter, the specimens were taken out of water. These samples were cured by moist jute bags for 7 and 28 days. The samples were tested after 7 and 28 days respectively for compressive strength as per the provisions of IS: 3495 (Part 1)–1992. The water absorption of the bricks was tested as per the provisions contained in IS: 3495 (Part 2)–1992. Before testing, the frogs and voids of the specimen were filled up with cement sand mortar (1: 1).

3. OBSERVATIONS The variation of compressive strength of bricks specimen with moulding pressure for different lime content at 7 and 28 days are shown in Figure1 and Figure 2, respectively. Figure 3 shows the variation of water absorption of bricks with moulding pressure for all the brick types.

[15] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

5 5 4 4 3 3 L:FA (20: 80) L:FA (20: 80) 2 2 L:FA (30: 70) L:FA (30: 70) (MPa) 1 (MPa)

(MPa) 1 1 L:FA (40: 60) 0 L:FA (40: 60) 0 0 kN 10 kN 30 kN 50 kN 0 kN 10 kN 30 kN 50 kN Compressive Strength Compressive Compressive Strength Compressive Compressive Strength Compressive Moulding Pressure Moulding Pressure

Fig. 1: Compressive Strength of L-FA Bricks at 7 Days

8 8 6 6 4 L:FA (20: 80) 4 L:FA (20: 80) L:FA (30: 70) 2 L:FA (30: 70)

(MPa) 2 (MPa) (MPa) L:FA (40: 60) 0 L:FA (40: 60) 0 0 kN 10 kN 30 kN 50 kN 0 kN 10 kN 30 kN 50 kN Compressive Strength Compressive Compressive Strength Compressive Compressive Strength Compressive

Fig. 2: Compressive Strength of L-FA Bricks at 28 Days

40 40 30 30 20 L: FA (20: 80) 20 L: FA (20: 80) 10 L: FA (30: 70) 10 L: FA (30: 70) L: FA (40: 60) 0 L: FA (40: 60) 0 0 kN 10 kN 30 kN 50 kN 0 kN 10 kN 30 kN 50 kN Water (%) Absorption Water (%) Absorption Water (%) Absorption Moulding Pressure Moulding Pressure

Fig. 3: Water Absorption of L-FA Bricks at 28 Days

4. DISCUSSIONS

Figure 1 and 2 show that increase in lime proportion increases the compressive strength of bricks at both 7 and 28 days. Also, this figure shows that the moulding pressure has an important effect on strength. The effect of moulding pressure on strength increases with the pressure. On pressure application the strength gain is more in case of bricks with larger lime proportion. The lime proportion does not influence much the strength and water absorption in case of hand moulded bricks (zero moulding pressure). Bricks having L: FA compositions of 30:70 and 40:60satisfies the requirements of class 3.5 and class 5 of IS: 12894-2002, respectively, when compressive strength at 28 days is considered. Bricks with L: FA composition 40:60 and moulded at 50 kN pressure belongs to class 3.5 when compressive strength at 7 days is considered.

[16] Fly Ash Bricks: Pressure Effect Increase of lime content decreases water absorption capacity of bricks as shown in figure 3. Brick with L:FA compositions 40: 60 is the only one satisfying the criteria of water absorption requirements of IS: 12894-2002.

5. CONCLUSION 1. The compressive strength of the bricks increases with increase in lime proportion. 2. The increased moulding pressure results in the increase of compressive strength and reduction in water absorption. 3. Of all the bricks, the one having L:FA composition of 40:60 satisfy the criteria of compressive strength and water absorption of IS: 12894-2002, (class 5).

REFERENCES [1] Sumathi, A., Raja Mohan, Saravana, K., (2015), “Compressive Strength of Fly Ash Brick with Addition of Lime, Gypsum and Quarry Dust”. In: International Journal of ChemTech Research CODEN (USA): IJCRGG I, Vol. 7, No. 01, pp. 28-36. [2] Hwang, Chao-Lung & Huynh, Trong-Phuoc. (2016). “Evaluation of the Performance and Microstructure of Ecofriendly Construction Bricks Made with Fly Ash and Residual Rice Husk Ash”. [3] Nataatmadja, Andreas. (2019). “Development of low-cost fly ash bricks”, pp. 831-843. [4] V. Karthikeyanand M. Ponni(2006), “An Experimental Study of Utilization of Fly Ash for Manufacturing of Bricks”, 22nd National Conference of Architectural Engineers Trichur, November 01-02, 2006. [5] ShardaDhadse, PramilaKumari and L J Bhagia (2008), “Fly ash characterization, utilization and Government initiatives in India – A review”, Journal of Scientific & Industrial Research, Vol. 67, January 2008, pp. 11-18. [6] Om Prakash (1990), “Utilization of Pulverized (Fertilizer Plant) Fly Ash as Low-Cost Bricks and Construction Material” M.Tech. Thesis Submitted to MNREC, Allahabad. [7] IS: 6932-1973, Methods of tests for building lime—Specification, Bureau of Indian Standards, New Delhi. [8] IS: 3495 (Part 1 and 2)-1992, Methods of tests of Burnt Clay Building Bricks—Specification, Bureau of Indian Standards, New Delhi. [9] IS: 12894-2002,Pulverized Fuel Ash-Lime Bricks—Specification, Bureau of Indian Standards, New Delhi.

[17] Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review

Saurabh Kumar1 and A.R. Quaff2 1Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Associate Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT The upflow anaerobic sludge blanket (UASB) process has emerged to be a feasible, economical and sustainable option for treatment of domestic wastewater in developing countries. In spite of their great advantages, UASB process failed to meet the desired disposal standards and required subsequent post treatments. In order to improve the efficiency of UASB based sewage treatment plants (STPs), suitable options are needed which should be efficient, economical and adequate. Hence, this paper discusses the different options for the treatments of effluents from UASB reactor treating domestic wastewater. Additionally, post treatments technologies recently used in India are also discussed. Keywords: UASB, Post Treatment, Domestic Wastewater, Water Treatment Sludge, STP

1. INTRODUCTION The UASB reactor is much popular in tropical countries due to low capital investment, low maintenance cost, less sludge production, less energy and land requirements and the potential to generate biogas [1]. In spite of their great advantages, UASB reactors removes nutrients i.e. nitrogen and phosphorus in less amount and does not meet disposal standards [1, 2]. In India, 37 STPs are using UASB technology at present. Among them, 22 are not confirming to disposal limits and most of them are located in Uttar Pradesh and Haryana [3]. Thus, post-treatment step is essential before discharge of UASB effluents into water bodies or for use in irrigation purpose. The main motive of the post-treatment step is to polish the organic matter, as well constituents such as nutrients (N and P) and meet the disposal standards. Different post treatment options for UASB effluents are available, such activated sludge system, hanging sponge method, flotation, aeration, and coagulation and stabilization ponds [1, 2, 4]. The proper and efficient choice of post treatment method is a great challenge because some methods require large area like stabilisation pond and some others are energy intensive [4,5]. This paper discussed the different options available for the treatments of effluents from UASB reactor treating domestic wastewater.

2. MAIN POST-TREATMENT OPTIONS CURRENTLY IN USE IN INDIA The post-treatment systems for treatment of UASB effluents are currently using in India are (i) Polishing ponds (ii) Activated sludge process (iii) Down-flow hanging sponge (DHS) reactor (iv) Aeration + Polishing pond (v) Coagulation-flocculation. Out of 37 UASB treatment plants, most of treatment plants uses polishing pond as a post treatment method [5]

2.1 Polishing Ponds (PP) A polishing pond is a large earthen basin in which wastewater is treat by natural purification process to provide necessary degree of treatment. The main advantage of polishing pond is to remove the pathogenic impurities present in the wastewater at a higher efficiency. Polishing ponds are mainly used to improve the quality of effluents from anaerobic treatment plants like UASB reactors. [18] Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review The polishing pond is also used as post treatment option for UASB effluents and in India, most of UASB based STPs used polishing pond as post treatment of UASB effluents. The combination of UASB reactor and polishing pond is one of the solutions in economical and environmental point of view but the main disadvantage is its excessive land requirement. Other researchers studied 10 UASB sewage treatment plants (STPs) situated at different cities of India. Out of 10 UASB treatment pants, 5 plants [Noida (27 MLD, 34 MLD), Saharanpur (38 MLD), Karnal (40 MLD) and Agra (78 MLD)] used polishing ponds (PP) as post treatment method for UASB effluent. These polishing ponds are operated at Hydraulic Retention Time (HRT) of 1 to 2 days. The combined (UASB+PP) system removed BOD, COD and TSS up to 10-52%, 33-46% and 21-57% respectively. The removal of ammonia was also found insignificant except at the Agra STP. About 76% removal efficiency of ammonia was observed at Agra STP plant and at other plants removal efficiency varied from 6 to 24%. Coliforms and phosphorus removal was also very low. Results indicated that the combination of UASB reactor with polishing pond is not successful to meet disposal standards for organic solids, nutrients and coliforms. This combination shows poor result in case of phosphorus and coliforms removal. The poor performance might be due to improper designed and variation in the characteristics of influent and lower hydraulic retention time of ponds. According to Survey of Central Pollution Control Board New Delhi on UASB based STPs, it is found that combined polishing pond with UASB show poor result [3]. In 2013, Central Pollution Control Board, New Delhi also reported the reason for poor performance of polishing pond based STPs. There is only one unit of this pond (no standby unit) has been provided in most of combined UASB+PP treatment plants. In such cases, it is difficult to clean off the deposited sludge without stopping the process. So in order to increase the efficiency of combined system at least, two units of such ponds are provided at each STP and operated at higher HRT.

2.2 Activated Sludge Process (ASP) The activated sludge process is type of aerobic process for treating wastewater using aeration and aerobic bacteria. On the basis of mixing conditions of aerobic activated sludge in aeration tank, activated sludge system can be classified as modern system and conventional activated sludge system. Khan et al. [6] evaluated the performance of 10 UASB reactor situated in different cities of India, out of which 2 reactors adopted activated sludge system as the post treatment of UASB effluents. 43 MLD STP, Vadodara (Gujarat) used surface aerators and 100 MLD STP, Surat (Gujarat) used diffused aerators for aeration. It is found that both ASP are capable to achieve wastewater disposal standards for organic impurities (COD, BOD, SS) and nitrogen but coliforms and phosphorus in final effluent found more than disposal standard. Therefore, on the basis of above research it can conclude that the combined UASB and ASP configuration was recommended to be a good alternative for meeting disposal standard in term of COD, BOD and SS.

2.3 Down-flow Hanging Sponge (DHS) Reactor DHS reactor can be a good option as aerobic post treatment of UASB effluents. In this reactor, sponge cubes are diagonally linked through nylon string and also cubes provided a large surface area to accommodate microbial growth under non–submerged conditions. In this system, the wastewater trickled through the sponge cubes and oxygen is supplied through natural flow of air in the downstream without any equipment. There is no need of external aeration in this system.

[19] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Based on this system, Khan et al. [6] checked the performance of UASB reactor in which DHS was used for polishing the effluents. 1MLD capacity of DHS reactor was installed at 40 MLD capacity of UASB reactor at Karnal (Haryana). The values of BOD, COD, TSS, ammonia in final effluent through combined (UASB + DHS) system observed lower than permissible disposal standard value. In other study, some researchers evaluated the performance of combination of UASB and DHS system. The removal efficiency of BOD, COD, and TSS observed as 96–98%, 91–98% and 93–96% at an overall HRT of 8 h. The final effluent values of BOD, COD and ammonia were found lower than permissible limit. But the combined system failed in case of coliforms and nutrients [7]. Results show that the DHS system was highly efficient for the removal of COD, BOD and TSS and not for nutrients.

2.4 Aeration + Polishing Pond It is extended form of polishing pond and in this system oxygen is provided by two ways i.e. (i) by natural way (photosynthesis form) (ii) by aerators. The removal efficiencies of parameters such as BOD, COD, TSS and coliforms by this system are higher than Polishing pond system but failed in removal of nutrients. Khan et al. [6] checked the performance of three STPs (111, 152 and 48 MLD) situated in Ludhiana. All three STPs adopted aeration followed by polishing pond as the post treatment of UASB effluents. The removal efficiency of BOD, COD and TSS was found greater than polishing pond system but the final effluent contained high nutrients and coliforms at all three STPs. The results show that aeration combined with PP is efficient for organic impurities but not feasible option for nutrients and coliforms removal.

2.5 Coagulation and Flocculation The purpose of coagulation-flocculation is to remove finely divided suspended solids and colloidal material from the waste liquid. Alum, ferric chloride, polyaluminium chloride (PACl) and ferric sulphate are commonly used coagulants. Many researchers suggest that the coagulation-flocculation method is feasible option as a post treatment for the UASB effluent. Due to high cost of coagulant, coagulation-flocculation system may not be a good option for post-treatment of UASB effluents and there is need of low cost of coagulants used for post treatment to overcome the disadvantages of coagulation-flocculation process [8]. Nair and Ahammed [9] used water treatment sludge (WTS) as coagulant with poly aluminium chloride and found BOD removal, suspended solids removal and phosphate removal observed 78%, 84% and 79% respectively. The results suggest that the reuse of WTS as a coagulant for the post-treatment of UASB effluent would be an economical option. For quick look the Table 1 and Figure 1 shows that the post treatment technique adopted by UASB reactor installed at different location in India. The Pi chart shows that In India, most UASB reactor adopted polishing pond as post-treatment technique.

[20] Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review

UASB + PP

UASB + ASP

UASB + DHS

UASB + FL +CL UASB alone

Fig. 1: Post Treatment Techniques Used in India

Table 1: Location and Capacity of UASB Reactors based Treatment Plant Situated in India UASB Reactor Followed Location of STP, Capacity (MLD) by Post–Treatment Karnal (48MLD), Faridabad (45MLD), Faridabad (20MLD), Agra (78MLD), Faridabad (50MLD), Gurgaon (30MLD), Panipat (10MLD), Panipat (35MLD), Noida (27MLD), Noida (34MLD), Sharanpur (38MLD), Jaj-mau (5MLD), Ghaziabad (56MLD), Ghazibad (70MLD), UASB+PP Chandigarh (22.73MLD), Sonipat (30MLD), Yamunanagar (10MLD), Yamunanagar (25MLD), Ludhiana (152MLD), Ludhiana (111MLD), Ludhiana (48MLD), Jalandar (100MLD), Mirzapur (14MLD) UASB+ASP Surat (100MLD), Vadodara (86MLD) UASB+DHS Karnal (48 MLD) UASB+FL+CL Ahmedabad (106MLD), Ahmedabad (126MLD) UASB+DHS+PP Karnal (48 MLD)

3. OTHER POST TREATMENT TECHNIQUE FOR UASB EFFLUENTS

3.1 Constructed Wetland (CW) The constructed wetland system accepted as economically and technically feasible option for wastewater treatment for small communities [10]. Simple construction, easy to operate, low maintenance and utilisation of natural processes are the advantages Constructed wetlands [11] Many reseachers used constructed wetland as post treatment method for UASB effluents. In the study, they used three units in constructed wetland system. Out of three units, unit A was used as control unit and units B and C were planted with wetland plants, namely Phragmites, mauritianus and Typha latifolia respectively. The average HRT adopted in units A,B and C were 1.85,1.96, and 1.99 days respectively. The performance of the vegetated units B and C were found better than the unit A. Nutrients removal were found low in all units. Ammonia (NH4-N) removal was obtained 11.2%, 25.2% and 23% in units A, B and C, respectively. The removal of COD was 33.6%, 56.3% and 60.7% for units A, B and C, respectively [11].

[21] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) De Sousa et al. [12] adopted the constructed wetland system for the post treatment of effluent of UASB reactor. It was used for the removal of residual organic matter, suspended solids, nutrients (nitrogen and phosphorus) and faecal coliforms in Brazil. The UASB reactor has 1500 L capacity and reactor was operated at varied HRT (3h and 6 h) and the UASB effluent was treated in four parallel units of artificial wetlands with coarse sand under different hydraulic and organic loads. Each of unit was 10 m long and 1.0 m wide. In three constructed wetlands, Macrophytes (Juncus sp.) were planted, whereas one constructed wetland was operated without plants. Removal efficiency of phosphate, nitrogen and faecal coliforms observed higher in planted constructed wetlands due to presence of microphytes. Hence planted constructed wetland with microphytes is better option compared to constructed wetland without plant.

3.2 Duckweed Pond Duckweed Pond is an aquatic macrophyte based treatment system. In duckweed pond system, ponds are covered by floating mat of macrophytes. In this system, nutrients are removed from the system by regular harvesting of the biomass and the produced biomass used as fodder for poultry and fish. El-Shafai et al. [13] used combination of a UASB reactor (6-h HRT) followed by three duckweed ponds in series (total HRT 15 days) and observed the performance of duckweed pond in warm and cold season. It observed that the overall efficiency of COD, BOD and TSS through the combined system was not significantly affected by temperature but the nutrient and faecal coliform removal was observed poor in winter due to reduction in growth rate of duckweed.

3.3 Dissolved Air Flotation (DAF) The main principle of DAF system is to treat the wastewater by dissolving air in wastewater under pressure and then air is releasing at the atmospheric pressure and then air forms tiny bubbles released in a flotation tank. Tiny bubbles are adhering to the suspended matter and causing the suspended impurities to float to the surface of the wastewater and then form a froth layer and layers are removed by a skimming device. Most of the time, the feed water passed through flotation tank dosed with coagulants to flocculate the suspended matter. Penetra et al. [14] determined the performance of a lab scale coagulated DAF system as the post treatment technique of UASB effluents. Ferric chloride (FeCl3) used as the coagulants in flotation tank and its dosages varied from 30 to 110 mg/L and pH was also varied from 5.3 to 6.1. The DAF system performed well at FeCl3 dose of 65 mg/L. The combined UASB-DAF system removed COD, total Phosphorus, TSS and Turbidity greater than 90%. DAF was found to be an attractive alternative to reduce COD, total Phosphorus, TSS and turbidity from the UASB effluent but not for coliforms.

3.4 Trickling Filter The anaerobic effluents are generally failed to meet disposal standards in terms of nitrogen as ammonia and organic matter removal. TF can remove organic matter and suspended solids in satisfactory amount and also meet the desired disposal standards for organic matter and suspended solids but nitrogen removal from UASB effluents is less. Chernicharo and Nascimento [15] evaluated the performance of TFs as post treatment of the UASB effluents. The average HRT of UASB reactor was taken 4 hours and also evaluated the performance at low, intermediate and high organic loading rate. The combined UASB-TFs system removed BOD, COD and SS very efficiently under low organic loading conditions. At high rate conditions the system was not

[22] Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review good to remove the COD, BOD and SS. The results of this study concluded that the TF can be good choice for the post treatment option for the treatment of UASB effluent at lower organic rate for removal of organic pollutants in tropical countries.

3.5 Trickling Filters Filled with Plastic: Or Sponge-based Packing Media In this treatment, to enhance the performance of simple trickling filter in term of nitrogen removal and for modification in TFs, sponge based packing medium is added in the system. Almeida et al. [16] investigated the performance of post treatment of UASB effluents by the two trickling filters with different sponge based packing medium. One trickling filter was filled with Rotosponge sponge medium and other contained Rotopack as sponge based packing medium, operated at HRT 0.3 and 2 h respectively. The UASB reactor treated the domestic wastewater from the Arrudas wastewater treatment plant (Belo Horizonte - Minas Gerais - Brazil) and the reactor was operated at HRT of 9 hours.

The combination UASB/TF-Rotosponge was achieved more removal of BOD, COD, TSS and NH4-N than UASB/TF Rotopack. TF-Rotosponge achieved 80% ammonium-N removal but in case of TF-Rotopack

NH4-N removals was found 40-50% because of enhanced oxygen availability inside the sponges and longer SRT. From the technology point of view UASB treatment with TF-Rotosponge is feasibly better option for removal of organic pollutants and nitrogen at large wastewater treatment plants.

3.6 Moving Bed Bio-film Reactor (MBBR) Other researchers investigated the performance of integrated UASB and MBBR reactor in Egypt for domestic wastewater treatment under temperature range of 22–35oC. UASB and MBBR operated for a period of 290 days at three different combined HRTs, 13.3 (8+5.3), 10 (6+4) and 5.0 h (3+2). Volumes of UASB reactor and MBBR were 10 and 8.0 L respectively. The removal efficiencies of total COD and coliforms reported higher at higher HRT (13.3h) and suspended solid removal was found independent of HRT. Overall reduction of total COD was 80–86% at the HRT of 5-10 h and increased up to 92% at HRT 13.3h.The removal of ammonia nitrogen was also calculated and the performance of combined UASB and MBBR system in term of ammonia nitrogen depends on organic loading rate. At lower organic loading rate, combined reactor was found more efficient and sludge production was also very less [17].

3.7 Aerated Fixed Bed Reactor (AFBR) Sumino et al. [18] evaluated the performance (in terms of only BOD, COD) of combination of UASB and aerated fixed bed reactor under constant HRT of 24 hrs in three different season summer, winter and autumn. In initial stage, sewage passed through a grit chamber and pre-treated by a denitrification (DN) reactor and then passed through a UASB reactor. The effluents of UASB reactor were post-treated by an AFB reactor under aerobic conditions, and the sludge was recirculated to the DN reactor. The DN reactor and the AFB reactor contained sponge sheets. The mean final effluent CODs were 54, 66 and 65 mg/L in the summer, autumn, and winter with mean final effluent BODs were 11, 18 and 25 mg /L in summer, autumn, and winter respectively. The final effluents BOD and COD observed in limit of disposal standards.

3.8 Sequential Batch Reactor (SBR) SBR is a fill and draw type activated sludge system and five common steps of fill, react, settle, decant and idle take place sequentially in single batch reactor. In this system wastewater is added to a single batch reactor to remove undesirable components.

[23] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Moawad et al. [19] adopted SBR as the post treatment of UASB effluents and studied the performance of mixed UASB-SBR system under different operating conditions for the treatment of domestic wastewater. The retention time in the UASB varied from 4 to 3 h and the aeration time in the SBR cycle was varied from 2 to 5 h, and then to 9 h and observed COD, BOD and TSS removal efficiency in range of 94–98% for the three runs. The final effluents concentration of COD, BOD, and TSS were 26, 5.8 and 5.0 mg/L, respectively. Nitrification of ammonia was completely achieved after 5 h aeration in the SBR. The average phosphorus removal was observed up to 65%. Final effluent concentration of FC was found 7.5 × 102 MPN/100 mL, when HRT was taken as 9 hrs. The results of combined UASB and SBR system state that the combination of UASB and SBR reactor could be a better option for the treatment of domestic wastewater.

3.9 Rotating Biological Contractors (RBC) A RBC contains an arrangement of a series of closely spaced polystyrene circular disks of plastic material and disks are partially submerged in wastewater. The breakdown and stabilization of organic pollutants is done by micro organisms grown on the surface of circular disks in presence of oxygen obtained from the atmosphere as the disks rotate. Soughing problems and development of excessive biofilm growth is responsible for poor performance of RBC and this is also the one of the major drawback of this technology. Low power requirements, excellent process control, the capability of handling a wide range of flows and low sludge production are the advantages of RBCs. Other researchers observed the performance of combined system of UASB-RBC system and found the removal efficiency of organic matter, nutrients and coliforms at different organic loading rates(OLRs) with constant HRT of 2.5 h and at different operational temperature (11, 20 and 30°C) . The system achieved better results at lower OLRs at 11, 20 and 30°C and RBC removed COD, ammonia and coliforms more at higher temperatures (30°C) [20]. Tawfik et al. [21] used the combination of a single stage RBC, two stages RBC and an anoxic up-flow submerged bio-filter as the post treatment of UASB effluents. This study was carried out to find the removal efficiency of COD fractions, E. coli, ammonia and nitrate removal. The final effluent of COD fractions, ammonia and E. coli content in the two stage RBC system were found lower than the effluent from the single stage RBC system.

3.10 Submerged Aerated Bio-Filter (SABF) The SABF system contains floating porous media and wastewater in which air flows through the porus media from the bottom of the reactor. The airflow direction in the SABF system is always upward but the liquid can flow either in upward or downward. These biofilters need backwash regularly at least once in 3 days. The main mechanism of biofilters is used to eliminate the soluble organic compound and suspended solids from the wastewater with the help of active, thin and homogeneous biofilm layer formation. This system is based on the attached growth mechanism. Gongalves et al. [22] used SABF of capacity 6.3 L as post treatment of UASB effluents. The UASB reactor of capacity 46L was initially operated at HRT of 8h and subsequently reduced to 4h. The removal efficiency of COD, BOD and SS through the combined was 91%, 96% and 94% respectively. The UASB-SABF system was found efficient in terms of organic matter removal but was not found good in case of the pathogenic microorganisms. In other study, Keller et al. [23] observed the performance of three submerged aerated biofilters (SABF) and one tertiary filter for the post treatment of UASB effluent. Tertiary treatment was done with the help of UV disinfection for polishing the coliforms. Effluents from SABF passed to UV disinfection and found coliforms in permissible limit.

[24] Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review

3.11 Membrane Technology An et al. [24] used the pilot scale cross flow membrane filtration system for post treatment of the effluent from UASB reactor of 34 L capacity treating low strength sewage. This was combined with a side stream membrane system and feed the UASB effluents with the help of centrifugal pump and observed change in the required parameter due to the effect of HRT. In this study, the HRT of UASB reactor was decreased from initial 10h to 5.5h after 119 days of operation. Increase in Biogas yield and COD removal was observed, when hydraulic retention time (HRT) of UASB was decreased. The COD removal efficiency was found 77.0% for the HRT of 10.0 h and 81.0% for the HRT of 5.5 h. Combination of membrane technology and UASB reactor can be work efficiently at low HRT than other post treatment.

3.12 Slow Sand Filtration (SSF) System SSF consist of a column, column has four section, the lower section of the column contains coarse gravel (4.75 mm) above 2 cm under drain of spherical glass balls and the coarse gravel was overlaid by 2 mm fine gravel layer which is followed 1.18 mm coarse sand layer along with 0.15 mm fine sand layer at the top. SSF is economical, simple in operation and efficient than other techniques but frequent cleaning and maintenance requirement is major drawback of this system when it is used as post treatment option. Various researchers operated SSF at different hydraulic rate and sand size, to check the effectiveness of UASB-SSF combined system. They found that SSF was capable to remove total coliform, turbidity, BOD and SS up to 99%, 88%, 86% and 68% respectively [25]. Recently, Tyagi et al. [26] used slow sand filter as a post treatment option at lab scale for the treatment of UASB effluents in which sand filter column was operated at hydraulic loading rate of 0.14 m/h and slow sand filters can be effectively operated up to 1 week at a hydraulic loading of 0.14m/h. Observed removal of FC, turbidity, TSS, BOD and COD was 99.99%, 91.6%, 89.1%, 85.0% and 77.0 % respectively. Result shows that slow sand filtration would be used as the post treatment for small-scale UASB reactor effluent in those countries, where treated effluent can be reused for gardening and irrigation due to excellent effluent quality.

3.13 Slow Sponge Sand Filter (SPSF) Maharjan et al. [27] used the two types of sand filters (SSF and SpSF) for tertiary treatment unit for the treatment of effluents through combined UASB and DHS system and also compared the performance of SSF and SpSF system. It was found that the SpSF system was more effective than conventional SSF under warmer conditions. During summer, final effluents concentration of TSS and BOD was approximately same. SpSF removed COD, total nitrogen (TN) and coliforms in more amount than SSF system. Whereas removal efficiencies of TN was found more in summer (62 ± 19%) than winter season (56 ± 13%). Both filters removed phosphorus in satisfactory amount. Results indicate that COD, nutrient and coliform removal in SpSF were relatively higher than conventional SSF, due to the increase in surface area of the sponges.

4. DISCUSSION The selection of proper, technically feasible, easy in operation and maintenance, economical and efficient post treatment method for polishing of UASB effluents treating sewage is a challenging task. Amongst all post treatment methods, first five methods (Polishing ponds Activated sludge process, Down-flow hanging sponge (DHS) reactor, Aeration + Polishing pond and Coagulation-flocculation) are generally used in different UASB based STPs situated in India. Most of the UASB based STPs used [25] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Polishing Pond as the post treatment technique for UASB effluents in India. The effluents from PP satisfied the effluent pathogen disposal standards but PP is not efficient in removing BOD, TSS and nutrient in high amount. Odour related problems, maintenance problem and large land requirement are major drawbacks of this post treatment technique. CPCB, New Delhi reported that many of UASB reactor based STPs has only one polishing pond unit and PP units were also found in very poor conditions due to lack of proper maintenance. It is very difficult to clean off the sludge deposits without stopping the process in single PP unit, so operation of single PP and improper maintenance are also responsible for poor performance. The combination of aeration and PP reduce the drawbacks of PP method by improving effluents quality in terms of BOD, COD and TSS but both PP and aeration-PP techniques removed negligible amount of nutrients. ASP and DHS methods are more efficient than PP, Aeration-PP for COD, BOD, TSS removal and satisfied disposal standards for BOD, COD and TSS. ASP and DHS also removed NH4-N in significant amount but these techniques are not efficient for phosphorus removal. High initial investment because of sponge cost, clogging of sponge cubes are the major drawbacks of DHS. Initial investment is high in case of ASP also. CL-FL technique is also used in some of UASB based STPs. CL-FL method is efficient in removing organic impurities, but less efficient in case of coliforms. This method is also costly because of high cost of coagulants and this drawback can be overcome by adding Water Treatment Sludge (WTS) as coagulant in system. WTS is waste of clariflocculator unit, contain coagulant properties, efficient to reduce required parameters, low of cost, therefore WTS is a good option as coagulant for this method.Other than these five methods , there is so many option in which some are advanced, some are economical, some are efficient than these five methods which are recently used as post treatment method at UASB based STPs in India. The constructed wetland and duckweed pond system are also efficient to polish the effluent quality because of good removal efficiencies of organic impurities and nutrients but less efficient for pathogen removal. Despite of good nutrient removal, these systems failed to bring down the effluent quality below discharging standards. Both methods also depend upon temperature, harvesting of plants and hydraulic load. DAF and CL-FL processes are capable of reducing organic impurities, turbidity and nutrients of UASB effluents up to the level of disposal standards but these processes are not efficient for removal of coliforms. The other disadvantages of these are large sludge volume generation, high dose and cost of coagulants used. Trickling filters are efficient to remove organic impurities at lower organic loading rate in tropical countries. Higher construction cost and lower nitrogen removal are the drawbacks of trickling filters. Addition of sponge-based packing medium enhanced the removal efficiencies of nitrogen. Trickling filters with Rotosponge packing medium is feasible option for removal of organic pollutants and nutrients than trickling filters. MBBR method was also found efficient to remove organic pollutants and nutrients at lower organic rate. Both ASP and SBR was found as the most suitable technology for the treatment of effluents of UASB reactor due to its high effluent quality and effluent organic pollutants follow discharging standards. Low energy consumption, efficient nutrient removal and low sludge production are the major advantages of SBR as compared to ASP and other post treatment techniques. AFBR is same as ASP but in AFBR pre treatment is done in denitrification (DN) reactor. AFB and DN reactors contain sponge sheet which increased the construction cost as compared to ASP but organic pollutants are within limit of disposal standard. Low power requirements, excellent process control, the capability of handling a wide range of flows and low sludge production are the advantages of RBCs but due to its tear and wear of moving parts, RBC is not generally used. Combined UASB + two stage RBC system was found more efficient for treatment of UASB effluents than combined UASB + single stage RBC system. For nitrogen removal, pre-anoxic biofilter unit is required. Similarly SABF system were found good for the removal of BOD, COD and SS but less efficient for nutrient removal.Slow sand filtration and membrane filtrations process are able to reduce organic pollutants, coliforms and nutrients nearer to disposal standards but frequent clogging of filters and membranes are main drawbacks of these systems. The performance of slow sand filtration system is enhanced by addition of sponge sheet. [26] Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review It is clear from the aforementioned literature review that the post treatment of an UASB effluent was done with conventional technology in which aerobic, anaerobic biological process was involved. All these processes would enhance the cost of treatment due to involvement of either large land area or power consumptions. The provision of proper wastewater treatment facilities have been the constant endeavour of previous researchers. A simple, economical alternative will contribute towards solving the problem of pollution. Comparative review of land requirement, O&M cost and capital cost, sludge generation, effect of climatic and environmental conditions, conformation of effluents with discharge standards, are summarized in Table 2 and Table 3.

Table 2: Comparison of Various Options of Integrated UASB Post-treatment Systems of Domestic Sewage in Term of Economic Aspect Economic Aspect Post Effects of Operation Treatment Construction Land Process Sludge Climatic Maintenance System Cost Requirement Reliability Generation Condition Cost ASP H A L H A L DHS H A L H A L CL+FL A H L H H NIL CW L L H L L H DP L L H L L H DAF A H L A H NIL TF A A L A A A AFBR H A L A A H SBR H A L H A L RBC A A L A A L SABF H A L A A L SSF A L A A L L

H = high; A = average; L= low; NR = not reported (4)

Table 3: Conformity of Effluent Parameters with Standards/Reuse Standards

Post Compliance with Stringent Effluent Standards/Reuse Standards Risk of Treatment Environmental System BOD & TSS Fecal Coliforms Nitrogen Phosphorus Problems ASP Y NR NR NR L DHS Y N N N L CL+FL Y N NR Y L CW N Y N N H DP N Y N N H DAF Y N N Y L TF N N NR NR A AFBR Y NR N N L SBR Y N Y Y L RBC N N N N L SABF Y N N N L SSF Y Y NR NR H

Y= yes; N = no; NR=not reported (4)

[27] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 5. CONCLUSION Finally, based on the overall study of various post treatment systems, it was concluded that there is no ideal post treatment technique which can fulfil to all conditions. Some techniques may be efficient, some may be economical and some may be easy in operation. Hence selection of technique must be decided on the basis of requirements. In India, out of 37 UASB based STPs, most of STPs adopted polishing pond as post treatment. The UASB system followed by polishing pond can be improved by proper maintenance and UASB based STPs can be upgraded by using advanced and emerging post treatment techniques which are discussed above. In economical point view, in India, Coagulation – Flocculation (WTS as coagulant) is best option for the treatment of UASB effluents.

REFERENCES [1] Chernicharo CAL (2006) Post-treatment options for the anaerobic treatment of domestic wastewater: Reviews in Environmental Science and Bio/Technology 5:73–92. [2] Tawfik A, El-Gohary F, Ohashi A, Harada H (2008). Optimization of the performance of an integrated anaerobic-aerobic system for domestic wastewater treatment. Water Sci. Technol 58: 185–94. [3] CPCB (Central Pollution Control Board) 2013 Performance evaluation of sewage treatment plants under NRCD, Delhi. [4] Khan AA, Gaur RZ, Tyagi VK, Khursheed A, Lew B, Mehrotra I, Kazmi AA (2011) Sustainable Post Treatment Options of Anaerobic Effluent. Resources, Conservation and Recycling 55: 1232– 1251. [5] Foresti E, Zaiat M, Vallero M, (2006) Anaerobic processes as the core technology for sustainable domestic wastewater treatment: Consolidated applications, new trends, perspectives, and challenges. Rev. Environ. Sci. Biotechnol 5: 3–19. [6] Khan AA, Gaur RZ, Mehrotra I, Diamantis V, Lew, B, Kazmi AA (2014) Performance assessment of different STPs based on UASB followed by aerobic post treatment systems. Journal of Environmental Health Science & Engineering 12:43. [7] Machdar I, Sekiguchi Y, Sumino H, Ohashi A, Harada H (2000) Combination of a UASB reactor and a curtain type DHS (downflow hanging sponge) reactor as a cost-effective sewage treatment system for developing countries. Water Science and Technology 42: 83–88. [8] Prakash K.J, Tyagi VK, Kazmi AA, Kumar A (2007) Post-treatment of UASB reactor effluent by coagulation and flocculation process. Environ. Prog. 26: 164–168. [9] Nair AT, Ahammed MM (2014) Coagulant recovery from water treatment plant sludge and reuse in post-treatment of UASB reactor effluent treating municipal wastewater. Environ Sci Pollut Res. 21(17): 10407-10418. [10] Okurut TO, Rijs GBJ., Van Bruggen JJA. (1999) Design and performance of experimental constructed wetlands in Uganda, planted with Cyperus papyrus and Phragmites mauritianus. Water Science and Technology 40(3): 265–271. [11] Kaseva ME (2004) Performance of a sub-surface flow constructed wetland in polishing pre-treated wastewater — a tropical case study. Water Research 38: 681–687. [12] De Sousa JT, Van Haandel AC, Guimarães AAV (2001) Post-treatment of anaerobic effluents in constructed wetland systems. Water Science and Technology 44(4): 213–219. [13] El-Shafai SA, El-Gohary FA, Nasr FA, Petervandersteen N, Gijzen HJ, (2007) Nutrient recovery from domestic wastewater using a UASB-duckweed ponds system. Bioresour. Technol. 98:798-807. [14] Penetra RG, Reali MAP, Foresti E, Campos JR (1999) Post-treatment of effluents from anaerobic reactor treating domestic sewage by dissolved-air flotation. Water Science and Technology 40: 137–143. [15] Chernicharo CAL, Nascimento MCP (2001) Feasibility of a pilot-scale UASB/trickling filter system for domestic sewage treatment. Water Science and Technology 44(4): 221–228. [16] Almeida GS, Ali A, Zahid R, Tyagi VK, Khursheed A, Lew B, Marcus AK, Rittmann BE, Chernicharo CAL, (2013) Performance of plastic- and sponge-based trickling filters treating effluents from an UASB reactor Water Science and Technology 67(5): 1034–1043. [17] Tawfik A, El-Gohary F, Temmink H (2010) Treatment of domestic wastewater in an up-flow anaerobic sludge blanket reactor followed by moving bed biofilm reactor. Bioprocess Biosyst Eng 33:267–276. [18] Sumino H, Takahashi M, Yamaguchi T, Abe K., Araki N, Yamazaki S, Shimozaki S, Nagano A, Nishio N (2007) Feasibility study of a pilot-scale sewage treatment system combining an up-flow anaerobic sludge blanket (UASB) and an aerated fixed bed (AFB) reactor at ambient temperature. Bioresour. Technol. 98: 177–182. [19] Moawad A, Mahmoud UF, El-Khateeb MA, El-Molla E (2009) Coupling of sequencing batch reactor and UASB reactor for domestic wastewater treatment.Desalination 242: 325–335. [20] Tawfik A, Zeeman G, Klapwijk A, Sanders W, El-Gohary F, Lettinga G, (2003) Treatment of domestic sewage in a combined UASB/RBC system. Process optimization for irrigation purposes. Water Science and Technology 48: 131–138. [21] Tawfik A, Klapwijk B, El-Gohary F, Lettinga G (2002) Treatment of anaerobically treated domestic wastewater using rotating biological contactor. Water Sci. Technol. 45: 371–376.

[28] Post-Treatment Options for Effluents of UASB Reactors Treating Domestic Wastewater in India: Review

[22] Gongalves RF, De Araújo VL, Chernicharo CAL, (1998) Association of a UASB reactor and a submerged aerated biofilter for domestic sewage treatment. Water Sci. Technol. 38: 189–195. [23] Keller R, Passamani-Franca RF, Passamani F, Vaz L, Cassini ST, Sherrer N, Rubim K, Sant’Ana T.D, Gonçalves RF (2004) Pathogen removal efficiency from UASB + BF effluent using conventional and UV post-treatment systems. Water Sci. Technol. 50: 1–6. [24] An YY, Yang F, Bucciali B, Wong F, (2009) Municipal Wastewater Treatment Using a UASB Coupled with Cross-Flow Membrane Filtration. Journal of Env. Engg.135: 86–91. [25] Ellis KV (1987) Slow sand filtration as a technique for the tertiary treatment of municipal sewages. Water Res. 21: 403–410 [26] Tyagi VK, Khan, AA, Kazmi AA, Mehrotra I, Chopra AK, (2009) Slow sand filtration of UASB reactor effluent: A promising post treatment technique. Desalination 249: 571–576. [27] Maharjan N, Kuroda K, Dehama K, Hatamoto M, Yamaguchi T, (2016). Development of slow sponge sand filter ( SpSF ) as a post-treatment of UASB-DHS reactor ef fl uent treating municipal wastewater Water Sci. Technol 74: 65–72.

[29] Determination of Liquefaction Potential of Sand-Fly Ash Blends

Deepak Kumar1 and Dr. Siddhartha Sengupta2 1Research Scholar, Department of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, India 2Associate Professor, Department of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, India E-mail: [email protected], [email protected]

ABSTRACT This paper intends to determine the liquefaction potential of sand mixed with different proportions of fly ash (0, 10, 20, 30, 40 and 50% by weight). Local river sand and fly ash from Inland Power Limited, Ramgarh, Jharkhand were used for the experiments. Different properties of sand and fly ash were determined, and the fly ash was categorized as Class F. Strain controlled cyclic triaxial laboratory experiments were performed on the sand-fly ash mixtures. All the samples were prepared at relative density of 40% by undercompaction method. The tests were performed at an effective confining pressure of 50 kPa and the shear strain applied was 0.75%. The frequency of the cyclic loading was fixed to 1 Hz. Liquefaction was said to occur when excess pore water pressure ratio became equal to effective confining pressure. The result of the experiments suggested that the addition of fly ash to sand had an inconsistent cyclic behavior. Initially the liquefaction resistance of sand-fly ash mixture decreased up to 20% of fly ash content, and then it increased up to 40% of fly ash content, and then again decreased for 50% fly ash content. The variation in number of cycles for liquefaction with different percentage of fly ash was plotted. The variation in shear modulus of the mixture has also been discussed in this study. Keywords: Liquefaction, Sand, Fly Ash, Cyclic Triaxial, Shear Strain, Pore Pressure

1. INTRODUCTION Liquefaction had been one of the major investigation subjects to geotechnical engineers in the recent past. Over the years, some of the most devastating and expensive damages to foundation of structures and dams were caused because of liquefaction of soil due to earthquake. Earthquakes of Bihar (1988), Bhuj (2001) observed by [1-2] explained the occurrence of liquefaction of soil beneath the foundations leading to collapse of buildings and slope failures. An intensive investigation of liquefaction potential of sand has been studied in the past [3-5]. Yoshimi et al. [6] studied the liquefaction resistance of clean sand by performing triaxial and standard penetration tests. Erten and Maher [7], Derakhshandi et al. [8], Takch et al. [9], Thevanayagam et al. [10] observed the cyclic behavior of sand. Studies related to improvement in liquefaction behavior of sandy soils have been investigated in the past. Noorzad and Amini [11] explored the liquefaction resistance of sand by adding polypropylene fiber and found that liquefaction resistance increased with increase in percentage of fiber. Porcino et al. [12] studied the liquefaction behavior of sands treated with cement and experienced increase in liquefaction strength. Stamatopoulos [13] determined the liquefaction strength of silty sands in terms of state parameters. However, the use of fly ash to determine the liquefaction strength of sand has not been investigated widely. Fly ash has drawn the attention of researchers in recent past. Prabakar et al. [14], Kaniraj and Havanagi [15] examined the effect of fly ash on strength of soil. Keramatikerman et al. [16] examined the improvement of liquefaction resistance of sand by the addition of fly ash and concluded that higher fly ash content increased the liquefaction resistance of sand. Kolay et al.[17] carried out stress-controlled triaxial test on sand-fly ash mixture containing different

[30] Determination of Liquefaction Potential of Sand-Fly Ash Blends percentage of fly ash and stated that liquefaction resistance first decreased and then increased with the fly ash percentage. It has been observed that the dynamic behavior of fly ash blended sand has not been investigated comprehensively till date. In the present paper strain controlled cyclic triaxial laboratory experiments are performed on sand-fly ash mixture to determine their liquefaction potential.

2. CLASSIFICATION OF MATERIALS

2.1 Sand Sand used in the test was collected from local river. Grain size distribution curve as per IS: 2720 (1985 reaffirmed 2006) [18] is shown in figure 1. The sand was classified as poorly graded sand (SP) according to Unified Soil Classification system. The scanning electron microscope (SEM) of sand presented in figure 2 shows that sand particles are angular in shape.

Fig. 1: Grain Size Distribution Curve of Sand The mean grain size of the sand used was 0.8 mm and the specific gravity of sand was determined as 2.6.

Fig. 2: SEM Image of Sand

[31] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.2 Fly Ash The fly ash used in the investigation was graded as class F fly ash and was obtained from Inland Power Limited, Ramgarh, Jharkhand. From the grain size distribution curve as shown in figure 3, it was found that the fly ash consists of mostly silt-sized particles. The specific gravity of fly ash was 2.17 and the loss on ignition value of fly ash was 3.30 %. The SEM image of fly ash seen from figure 4 revealed that the particles of fly ash are clustered.

Fig. 3: Grain Size Distribution Curve of Fly Ash

Fig. 4: SEM Image of Fly Ash Some of the major oxides and elements present and their concentrations in the fly ash as obtained from X-ray fluorescence test is shown in Table 1. Fly ash mostly consists of oxides of silica and aluminum.

Table 1: Major Oxide and Elemental Concentrations Present in Fly Ash Oxide Concentration Elemental Concentration Formula Concentration Formula Concentration

SiO2 63.70% O 50.91%

Al2O3 24.00% Si 29.78%

Fe2O3 3.23% Al 12.70%

TiO2 1.88% Fe 2.26%

K2O 0.90% Ti 1.13% CaO 0.80% K 0.75% [32] Determination of Liquefaction Potential of Sand-Fly Ash Blends 3. METHODOLOGY

3.1 Sample Preparation Under compaction method [19] has been used for the preparation of cylindrical sand-fly ash samples of 100 millimeters height and 50 millimeters diameter. Five different fly ash proportions (0, 10, 20, 30, 40 and 50% by weight) were used. The maximum and minimum void ratios for different compositions of sand-fly ash mixtures were calculated and presented in table 2.

Table 2: Index Properties of Sand Fly Ash Mixture at 40% Relative Density Composition Specific Gravity Maximum Void Ratio Minimum Void Ratio Sand + 0% Fly Ash 2.60 0.67095 0.36647 Sand + 10% Fly Ash 2.58 0.64990 0.36530 Sand + 20% Fly Ash 2.55 0.67430 0.38376 Sand + 30% Fly Ash 2.53 0.68890 0.38902 Sand + 40% Fly Ash 2.51 0.77630 0.46313 Sand + 50% Fly Ash 2.50 0.84620 0.48367 The dry weight was calculated from minimum and maximum void ratio of each mixture for 40% relative density. Sand-Fly ash mixtures were poured in to a cylindrical split mold in 5 layers and each layer was tamped to a fixed number of blows with a tamping rod. Filter papers and porous stones were placed on the top and bottom of sample. Prepared sample is shown in figure 5. Vacuum was continuously applied during the sample preparation. Once the sample was prepared, assembly was fitted the triaxial cell and filled with water.

Fig. 5: Prepared Cylindrical Sample

3.2 Test Equipment and Procedure Static cum cyclic triaxial testing machine manufactured by HEICO, India has been used to perform the strain controlled cyclic tests. There are three pipes connected to pneumatic control panel of the machine for the application of vacuum, cell pressure and back pressure. The instrument has two LVDTs to measure large and small strains respectively and a pore pressure transducer. The load is measured through a load cell and the parameter variations are recorded through an electronic data acquiring system. [33] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) After the preparation of the sample the confining and back pressures were applied for the saturation of the specimen. The samples were saturated up to 95% and with the increase in the percentage of fly ash, the time taken by the sample to achieve full saturation also increased. After saturation, the samples were subjected to consolidation and water from the sample was allowed to drain out. The typical time (min) versus volume change (cc) plot during consolidation stage is presented in figure 6.

Fig. 6: Volume Change with time During Consolidation Stage of the Sample Cyclic loading was then applied to the sample at shear strain of 0.75% and the frequency of the loading was kept 1 Hz. The effective confining pressure applied was 50 kPa. The sample was subjected to loading till the stress became zero and 100% pore pressure was achieved. Tests were performed as per [20–21].

4. RESULTS AND DISCUSSIONS

4.1 Initiation of Liquefaction of Sand-Fly Ash Mixture

Fig. 7: Variation in Pore Pressure Ratio with Number of Cycles for Sand + 10 % Fly Ash Mixture at 40% Relative Density The variation in excess pore pressure was plotted against number of cycles and presented in figure 7. Excess pore water pressure ratio was increased gradually from zero to one with the increase in loading cycle till liquefaction was initiated and after that it (pore water pressure ratio) became constant. The liquefaction cycle was identified when the excess pore water pressure ratio became equal to 1. [34] Determination of Liquefaction Potential of Sand-Fly Ash Blends It can be observed from figure 7 that pore pressure ratio showed a rapid increase till 10th cycle and after that the pore pressure ratio increase was almost constant before it became 1 at 35th cycle. This demonstrates that the voids in the sample get filled by the pore water very quickly with the application of the cyclic loading.

4.2 Variation in Liquefaction Resistance of Sand with Different Fly Ash Content Addition of fly ash to sand showed inconsistent behavior in liquefaction resistance. Number of cycles corresponding to liquefaction of sand was 40 which decreased from 35 and 25 for sand + 10 % fly ash, and sand + 20% fly ash mixtures respectively. On further addition of fly ash, number of cycles for liquefaction increased to 60 for sand + 40% fly ash blend and again decreased to 55 for sand + 50% fly ash mixture. Number of cycles to liquefaction for different percentage of fly ash is depicted in figure 8. This behavior can be most appropriately explained through sand skeleton void ratio [22] of sand which does not changed till 20% addition of fly ash. But after that sand gets more densified and liquefaction resistance increased.

Fig. 8: Variation in Number of Cycles for Liquefaction with Different Fly Ash Percentage

4.3 Behavior of Shear Modulus of Sand-Fly Ash Mixture

1.2 1 0.8 max 0.6 G/G 0.4 0.2 0 1 11 21 31 41 number of cycles

Fig. 9: Variation of G/Gmax with Cycle Number for Sand + 10% Fly Ash Mixture Shear modulus was calculated from the hysteresis loop of the stress strain curve as the slope of the line of the extreme points in the loop [23]. From the plot it was observed that the normalized shear modulus

(G/Gmax) tended to decrease with the increase in the number of cycles of loading. The decreasing trend of the shear modulus continued till the sample attained 100% pore water pressure ratio. Typical [35] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) graph of variation in normalized shear modulus with number of cycles for sand + 10 % fly ash mixture (corresponding to 40% relative density) is showed in figure 9.The stiffness of the sample degraded with loading because of increasing pore water pressure and hence the shear modulus decreased.

5. CONCLUSION The liquefaction resistance of sand-fly ash mixtures had been studied and discussed in this investigation. The physical properties of sand and fly ash were determined. Sand was classified as poorly graded while fly ash was categorized as class F. From the laboratory experiments performed the effect of fly ash addition on the liquefaction behavior of sand was investigated. The samples were said to be liquified when excess pore pressure and effective confining pressure were equal. The number of cycles for liquefaction was initially decreased up to 20% fly ash content but after that it increased for 30 & 40% fly ash proportions; again it decreased for sand + 50 % fly ash blend. The shear modulus of the mixture was studied and it was observed that the shear modulus had a decreasing tendency with number of cycles till liquefaction was achieved. A limitation of this study was that only one magnitude of effective confining pressure was considered.

REFERENCES [1] Mukherjee S, Lavania BVK (1998) Soil liquefaction in Nepal-Bihar earthquake of August 21, 1988. International conference on Case Histories in Geotechnical Engineering, 11, St. Louis, Missouri, pp. 587-592. [2] Ramakrishnan D, Mohanty KK, Nayak SR, Chandran RV (2006) Mapping the liquefaction induced soil moisture changes using remote sensing technique: an attempt to map the earthquake induced liquefaction around Bhuj, Gujrat, India. Geotechnical and Geological Engineering, 24:1581-1602. doi: 10.1007/s10706-005-3811-1 [3] Seed HB, Lee KL (1966) Liquefaction of saturated sands during cyclic loading. J Soil Mech Found Div ASCE, 92(SM6): (105-134) [4] Seed HB, Martin P, Lysmer J (1976) Pore-water pressure changes during soil liquefaction. J Geotech Eng Div ASCE, 102(GT4):323-346 [5] Amini F, Qi GZ (2000) Liquefaction testing of stratified silty sands. J Geotech Geoenviron Eng, 126:208-217 [6] Yoshimi Y, Tokimatsu k, Hosaka Y (1989) Evaluation of liquefaction resistance of clean sands based on high-quality undisturbed samples. Soils and Foundations, 29(1):93-104. [7] Erten D, Maher MH (1994) Cyclic undrained behavior of silty sand. Soil Dynamics and Earthquake Engineering, (14): 115-123 [8] Derakhshandi M, Rathje EM, Hazirbaba K, Mirhosseini SM (2008) The effect of plastic fines on the pore pressure generation characteristics of saturated sands. Soil Dynamics and Earthquake Engineering, (28):376-386 [9] Takch AEI, Sadrekarimi A, Nagar HEI (2016) Cyclic resistance and liquefaction behavior of silt and sandy silt soil. Soil Dynamics and Earthquake Engineering, (83):98-109. doi: 10.1016/j.soildyn.2016.01.004 [10] Thevanayagam S, Veluchamy V, Huang Q, Sivaratnarajah U (2016) Non-plastic silty sand liquefaction, screening, and remediation. Soil Dynamics and Earthquake Engineering, (91):147-149. doi: 10.1016/j.soildyn.2016.09.027 [11] Noorzad R, Amini PF (2014) Liquefaction resistance of Babolsar sand reinforced with randomly distributed fibers under cyclic loading. Soil Dynamics and Earthquake Engineering, (66):281-292. doi: 10.1016/j.soildyn.2014.07.011 [12] Porcino D, Marciano V, Granata R (2015) Cyclic liquefaction behavior of a moderately cemented grouted sand under repeated loading. Soil Dynamics and Earthquake Engineering, (79):36-46. [13] Stamatopoulos CA (2010) An experimental study of the liquefaction strength of silty sands in terms of the state parameters. Soil Dynamics and Earthquake Engineering, (30):662-678. doi: 10.1016/j.soildyn.2010.02.008 [14] Prabakar J, Dendorkar N, Morchhale R (2004) Influence of fly ash on strength behavior of typical soils. Const Build Mater, 18(4):263-267. [15] Kaniraj SR, Havanagi VG (1999) Compressive strength of cement stabilized fly ash-soil mixtures. Cem Concr Res, 29(5):673-377. [16] Keramatikerman M, Chegenizadeh A, Nikraz H (2017) Experimental study on effect of fly ash on liquefaction resistance of sand. Soil Dynamics and Earthquake Engineering, (93):1-6. doi: 10.1016/j.soildyn.2016.11.012 [17] Kolay PK, Puri VK, Tamang RL, Regmi G, Kumar S (2019) Effects of fly ash on liquefaction characteristics of Ottawa sand. International Journal of Geosynthetics and Ground Engineering, 5:6. doi: 10.1007/s40891-019-0158-x [18] IS: 2720 (1985 reaffirmed 2006) Methods of test for soils, part 4 grain size analysis. Bureau of Indian standards, New Delhi, India. [19] Ladd RS (1978) Preparing test specimens using undercompaction. Geotech Test J ASTM, 1(1):16-23 [20] ASTM D5311 (1992) Standard test method for load controlled cyclic triaxial strength of soil. ASTM, West Conshohocken, PA. [21] ASTM D3999 (1996) Standard test methods for the determination of the modulus and damping properties of soils using the cyclic triaxial apparatus. ASTM, West Conshohocken, PA. [22] Polito CP, Martin JR (2001) Effects of nonplastic fines on the liquefaction resistance of sands. J Geotech Geoenviron Eng ASCE, (127):408-415. [23] Kokusho T (1980) Cyclic triaxial test for dynamic soil properties of wide strain strange. Soils and foundations, 20(2):45-60

[36] Annual Average Rainfall Distributions in Bihar

Dr. Vikram Kumar Assistant Professor, Department of Civil Engineering, Gaya College of Engineering, Gaya, Bihar, India E-mail: [email protected]

ABSTRACT Average annual rainfall records from three rain gauge stations, Gaya, Patna and Patna in Bihar are investigated during 1901 to 2002 (102 years) to select the best suitable probability distribution (PD). Data of rainfall acquired from the Indian Water Portal (IWP). In this article, Maximum Likelihood Method (MLM) is used for approximation parameters of different distributions such as Normal, Gamma and Log Normal. Once the distribution for rainfall is estimated then it was tested using Kolmogorov-Smirnov (KS) test. On the basis of the KS test, Normal distribution has been found as the most suitable probability distribution to characterize yearly rainfall in these three regions of Bihar.

1. INTRODUCTION The measure of water accessibility in an area can be evaluated by numerous factors, for example, the rainfall of the region is one of the way. Consequently, it is a generous thing to deal with the water supply ideally in light of the fact that it majorly affects the economy and life of a locale. The measure of water supply that is too little will have a terrible effect for a zone, for example, dry season. In any case, the measure of water supply that is an excessive amount of can likewise cause flood events that meddle with day by day exercises, for example, flooding. To oversee water supplies, a comprehension of the attributes of rainfall as rainfall distribution is required. Sen et al. (1999) considered that the best PD of rainfall at monthly scale in Libya region is found as Gamma distribution which was confirmed on the basis of Chi-Squared test. Husak et al. (2006) in their study revealed that, drought monitoring can be done by studying the monthly PD of rainfall in Africa. He also confirmed from their study that, the Gamma distribution turns approximately best for the monthly rainfall distribution. Alghazali et al. (2014) in their study fitted thirteen (13) rainfall stations data in Iraq through three PD, such as Normal, Gamma and Weibull with a goodness of fit (GoF) test obtained from five of thirteen rainfall stations were Normal distributed. Mohamed et al. (2016) acknowledged an suitable PD of rainfall data for the period 1971 to 2010 from fourteen (14) rainfall stations in Sudan. It was establishing that the PD of Normal and Gamma is the best appropriate distribution. Based on the above research of Husak et al. Sen et al. Mohamed et al. and Alghazali et al. each using a commonly used distribution on different arid and semi-arid regions. As far as the authors knowledge, not any research been establishing on the Bihar region which are suffering due to drought because of low rainfall at some districts and on the other hand flood due to high rainfall in major districts. For that an attempt has been made to look at regions, namely Gaya, Patna and Muzaffarpur by taking samples of three rain stations data using commonly suggested probability distribution Normal, Log Normal and Gamma.

2. MATERIAL AND METHODS

2.1 Data Data of rainfall is acquired through the India Water Portal (IWP) during 1901 to 2002. The station is selected randomly to analysis the top three districts of the state. Picture 1-3 shows the histogram of stations Gaya, Patna and Muzaffarpur. [37] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 1: Probability Distribution Function and Histogram of Gaya Station

FIg. 2: Probability Distribution Function and Histogram of Patna Station

[38] Annual Average Rainfall Distributions in Bihar

2.2 Maximum Likelihood Fig. 3: Probability Distribution Function and Histogram of Muzaffarpur Stations Maximum Estimation Likelihood (MLE) is a technique which maximizes likelihood function. 2.2 Maximum Likelihood The principle followed is to choose as the point estimate for which maximizes L (X ; θ). 2.2 Maximum Likelihood Maximum Estimation Likelihood (MLE) isThe a technique MLE method which marks maximizes the likelihood likelihood function function. L (X ; θ) to be supreme by using logarithmic Maximum Estimation Likelihood (MLE) is a technique which maximizes likelihood function. The principle The principle followed is to choose as thefunctions. point estimate So the for likelihood which logarithm maximizes function L (X ; θis). denoted by . By using followed is to choose � as the point estimate for θ which maximizes L (X ; ). The MLE method marks logarithms L (X ; θ), the likelihood estimator is obtained from the likelihood function The MLE methodthe markslikelihood the likelihood function L function (X ; ) to L be(X supreme; θ) to be by supreme using logarithmic by using logarithmic functions. So the likelihood logarithm derivative of its parameters, that is θ functions. So thefunction likelihood is denoted logarithm by l(functionX; �) > lis(X; denoted θ). By byusing logarithms L (X; . ),By the using likelihood estimator is obtained 2.3 Normal Distribution logarithms L (Xfrom ; θthe), thelikelihood likelihood function estimator derivativeθ is obtained of its parameters, from the thatlikelihood is function θ derivative of its parameters, that is A random variable is said to be normally distributed , if and only if the density 2.3 Normal Distribution function is in the form of: 2.3 Normal Distribution A random variable is said to be normally distributed , if and only if the density µ, 2 (1) function is in theA formrandom of: variable X is said to be normally distributed X~N ( σ ), if and only if the density function is in the form of: where: expectation variance

(1) (1) where: expectation variance2.4 Gamma Distribution 2 σ : µ where: expectationBy presum ingvariance X is a continuous random variable, distributes gamma with parameters α and β, 2.4 Gamma Distribution in the case that, the PDF is in the form of:

By presuming X2.4 is a continuousGamma D randomistribution variable, distributes gamma with parameters α and β, (2) By presuming X is a continuous random variable, distributes gamma with parameters and , in the case in the case that, the PDF is in the form of: that, the PDF is in the form of: If a random variable X is said to be gamma distribution(2) α β then the mean and variance of the Gamma distribution are: (2) dan If a random variable X is said to be gamma distribution then the mean and variance of the Gamma distribution are: If a random variable X is said to be gamma distribution then the mean and variance of 2.5dan Log Normal Distribution: the Gamma distribution are: Suppose a random variable X is a positive real number ( 0 < x < ∞) such that Y = ln x is said to 2.5 Log Normal Distribution: be Log Normal distribution[39] with the expectation µ and variance σ2 . X = ey is a Log Normal Suppose a random variable X is a positive real number ( 0 < x < ∞) such that Y = ln x is said to be Log Normal distribution with the expectation µ and variance σ2 . X = ey is a Log Normal e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

dan

2.5 Log Normal Distribution Suppose a random variable X is a positive real number (0 < x < ∞) such that Y = ln x is said to be Log Normal distribution with the expectation µ and variance 2. X = ey is a Log Normal distribution or can be written as and. Since and y = N (µ, 2) are connected with the relation Y = ln x, then the density function of Log Normal distribution is: σ σ (4)

If a random variable X is a Log normal distribution then the mean and variance of the Log Normal distribution are:

dan

2.6 Goodness of Fit Test Goodness of fit test is used based on the complete cumulative distribution function with predetermined parameters. In this paper, an appropriate distribution model for the data will be determined using the Kolmogorov-Smirnov test. 4. Kolmogorov-Smirnov Test (KS-T) KS-T principal is comparing the function of empirical distribution with a special distribution function contained in the KS teat table. Testing hypothesis is as follow:

Kolmogorov Smirnov: H0: Dmax < D

H1: Dmax > D KS statistical test is shown in the following equation:

Dmax = Max |Pe - Pt|

With critical area refused H0 if D > D where: α

H0 = data distribution according to the selected distribution, H1 = data is not distributed according to the selected distribution; D = the critical value of form KS table

Dmax = the largest absolute difference between empirical probability and theoretical probability

Pe = empirical probability; Pe = theoretical probability

3. RESULTS AND DISCUSSIONS

3.1 Maximum Likelihood Method Parameter Estimation By using Likelihood Estimation, the parameters of three PDF (Normal, Log Normal and Gamma), are listed in table 1, which is as follow:

[40] Annual Average Rainfall Distributions in Bihar

Table 1: Parameter Value of Rainfall Distribution Normal Log Normal Gamma Stations µ σ µ σ α β Gaya 19.56 95.046 0.2197 4.531 23.124 4.1103 Patna 16.33 90.95 0.0189 4.4933 31.025 2.9318 Muzaffarpur 17.150 94.051 0.1883 4.5260 30.055 3.129

3.2 Kolmogorov-Smirnov Test KS testing norm is to match the value of D gained from the Kolmogorov- Smirnov critical table and the value of Dmax achieved using calculation, with 95% confidence interval, then: D = (1.36/sqrt(n))

Table 2: Critical Values D and Observations Dmax Kolmogorov-Smirnov D Station N max Normal Log Normal Gamma Gaya 120 0.123238 0.07518 0.11758 0.12884 Patna 120 0.123238 0.04918 0.8122 0.0699 Muzaffarpur 120 0.123238 0.05255 0.06166 0.0585

From the table 2, it can be perceived that the values of Dmax, in the Normal distribution for respectively station are a smaller amount than the value of D.

4. CONCLUSION An attempt was made to look at regions, namely Gaya, Patna and Muzaffarpur by taking samples of three rain stations data using commonly suggested probability distribution Normal, Log Normal and Gamma. On the basis of PDF, Normal distribution has been revealed as the most suitable distribution to represent monthly rainfall distribution in the three districts of the Bihar. On the basis of KS test results with 0.05 the three rain stations are Normally distributed. If considered from a critical value, then the Gamma distribution is rated second and the Log normal distribution is rated to last.

REFERENCES [1] Mood A M, Graybill F A and Boes D C 1974 Introduction to the Theory of Statistics (New York: McGraw-Hill) [2] Aitchison J and Brown J A C 1963 The Log Normal Distribution With Special Reference To Its Uses In Economics (Great Britain: Cambridge University Press) [3] Hann C T 1977 Statistical Methods in Hydrology (Ames: The Iowa State University Press) [4] Husak G J, Michaelsen J and Funk C 2006 International Journal of Climatology 27 935 [5] Jamaluddin S and Jemain A A 2007 Journal of Applied Sciences 7 1880 [6] Mohamed T M and Ibrahim A A A 2016 SUST Journal of Engineering and Computer Sciences 17 34 [7] Alghazali N O S and Alawadi D A H 2014 Civil and Enviromental Research 6 40. [8] Ozturk A 1981 Journal of Applied Meteorology 20 1499 [9] Sen Z and Eljadid A G 1999 Hydrological Sciences Journal 44 665. [10] Sharda V N and Das P K 2005 Agricultural Water Management 76 120. [11] Thom H C 1958 Monthly Weather Review 86 117. [12] Walpole R E, Myres R H, Myres S L and Ye K 2007 Probability & Statistics for Engineers and Scientists (United States: Prentice Hall). [13] Wilks D 1990 Journal of Climate 3 1495. [14] Wong R K W 1977 Journal of Applied Meteorology 16 1360.

[41] Concrete with Hybrid Polypropylene-Nylon Fibers

Mani Mohan1, Anurag2 and Sagar Sarangi3 1Assistant Professor, Department of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, India 2,3Research Scholar, Department of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, India E-mail: [email protected], [email protected]

ABSTRACT Synthetic fibers in concrete are an inexpensive and cost-effective solution to perform as crack arrestor along with improved mechanical properties in concrete. In this paper, mechanical properties of concrete with different proportion of fibers of Polypropylene, Nylon and hybrid fiber obtained from mixing of polypropylene and Nylon fibers to obtain a single matrix has been carried out. This work aims to determine the optimum proportion of mixture of polypropylene and Nylon fibers (hybrid fibers) in concrete, which results for better compressive, tensile and flexural strength. Concrete of grade M20 is used to cast 150mm cubes, 150mm x 300mm cylinder and beams of dimensions 500m x 100mm x 100mm with different proportion of fibers of Polypropylene, Nylon, and hybrid fibers. Based on the experimental results it is being determined that hybrid fiber concrete (HFC) obtained by nylon and polypropylene combinations in concrete gives improved mechanical properties compared to nylon or polypropylene fiber reinforced concrete (FRC). Keywords: Fiber, Hybrid Fiber Concrete, Polypropylene, Nylon, Flexural Strength, Compressive Strength, Split Tensile Strength

1. INTRODUCTION Concrete in spite possessing low toughness and tensile strength is used extensively as a construction material. In plain concrete, structural cracks develop even before loading due to drying shrinkage and other causes of volume change. Incorporation of fibers in concrete enhances the tensile capacity as well as the toughness of the resulting Fiber Reinforced Concrete (FRC). The formation of plastic shrinkage cracks in concrete gets arrested because of the uniformly distributed fibers in the fresh concrete. In the hardened concrete, the uniformly distributed fibers reinforce microcrack from developing into macrocracks. Polypropylene (PP), polyethylene (PE), polyvinyl alcohol (PVA), polyvinyl chloride (PVC), nylon, aramid, and polyesters are commonly used short synthetic fibers in concrete members and several studies have been performed on concrete with mono-fiber reinforcement i.e. FRC [1-3]. Among all synthetic fibers available PP fibers have been used widely for construction activities such as in pavements, overlays, blast resistant concrete and shotcrete. It has been reported [4] that adding 0.2 – 0.3% collated fibrillated PP fibers by volume, acted as crack arresters in the concrete mix, preventing cracking propagation in the plastic as well as in the hardened state. PP fibers also slightly increased the flexural (tensile) strength of the concrete. There was an improvement in ductility and post-crack energy absorption capacity (toughness) too. Another study [5] indicates an enhancement of flexural (tensile) strength up to 1.5% volume of PP fiber beyond this volume there was a drop in tensile strength of FRC. Nylon fiber has also been used and it has been reported [6] that nylon fiber reinforced concrete possess better mechanical properties than PP fiber reinforced concrete. Mono fiber use in concrete may be effective only for a small range of crack growth rate and strain, hence, may show less improvement of strength or ductility of concrete. To counter the same, widespread attention on the use of hybrid short fibers in a suitable proportion as reinforcement in concrete i.e. Hybrid fiber concrete (HFC) has gained attention to achieve desired benefits over FRC. HFC provides an option of [42] Concrete with Hybrid Polypropylene-Nylon Fibers achieving a blend of properties such as stiffness, ductility, and strength, which cannot be achieved by FRC. HFC consists of the use of two or more fibers to obtain a single matrix in concrete. The possible combination of fibers includes synthetic-synthetic, natural-synthetic and natural-natural types. The majority of published studies are restricted to the use of mono fibers alone in concrete or in combination with steel fibers [7-12]. Fresh and hardened properties of HFC concrete with polyolefin (PO) and PP synthetic fibers investigation indicated improved compressive and tensile strength with better durability for hybridization of 0.9% by volume of PO fibers with 0.1% by volume of PP fibers [13]. Negative effect on the properties of concrete is being observed in the use of high-volume fractions of the PO with PP fibers hybridization. Limited data are available on the optimum proportion of PP fiber with nylon fiber to acquire desired mechanical strength benefits. This paper aims to fill the gap by determining the optimum percentage by volume combination of PP and nylon fiber on the basis of compressive, tensile and flexural strength.

2. EXPERIMENTAL WORK

2.1 Materials A commercial 43 grade Ordinary Portland cement (OPC) manufactured by Emami cement limited conforming to the requirements specified in IS 8112:2013 [14] was used for all mixes. Locally available clean and dry river sand with a fineness modulus of 2.78 was used as fine aggregate. Natural crushed stone with a maximum size of 20 mm was used as coarse aggregate. Two different types of fiber polypropylene fiber provided by the M/S Bajaj Reinforcement LLP, Nagpur, Maharashtra, India; and nylon fiber supplied by Polyventure, Kolkata West Bengal India were used. The characteristics of fibers are given in Table 1. The concrete mix was prepared using normal tap water

Table 1: The Properties of Fibers

Property Polypropylene Nylon Length (mm) 6 18 Diameter (mm) 0.1 0.01 Specific gravity 0.91 1.13 Tensile strength (MPa) 400 815 Elastic modulus (GPa) 3.5 4.7 Water absorption Nil 4%

Fig. 1(a): Polypropylene Fiber Used Fig. 1(b): Nylon Used

[43] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.2 Characterization of Cementitious Material and Aggregates Physical properties of OPC used is being determined following the methods prescribed in Indian standards and it is being presented in Table 2. Aggregates physical properties are tested as per specifications laid by Indian standard [15] and is given in Table 3.

Table 2: Physical Properties of OPC Requirement as Per IS: 8112-1989 Test Parameter Results (BIS 2013) Fineness Specific Surface Blaine (m2/Kg) 265 225 Vicat time of setting (min)-initial 95 30 Vicat time of setting (min)-final 244 600 (max) Compressive strength (MPa) 3 days 27.6 23 (min.) 7 days 36.4 33 (min) 28 days 45.4 43 (min)_ Specific gravity 3.11 -

Table 3: Physical Properties of Aggregates Property Fine Aggregate Coarse Aggregate Specific gravity 2.56 2.89 Fineness modulus 2.78 6.97 Water absorption (%) 1.8 0.4

2.3 Mixture Proportions and Fresh Concrete Properties M20 grade concrete mix proportion was calculated based on guidelines of Indian standards [16]. Three control samples of 150mm x 150mm x 150mm concrete cubes, 150mm x 300mm cylinder and beam sample of dimensions 500m x 100mm x 100mm were prepared without adding any fibers. Concrete cube and beam specimens using mono-fiber as polypropylene and nylon at a volume fraction of 0.1 %, 0.3%, 0.5%, 0.7% are employed in concrete to obtain FRC. A hybrid mix consisting of a PP and nylon fiber with 1% and 2% as total fiber volume fraction in mixtures is considered in the concrete mix to obtain HFC. Water to cement ratio (w/c) considered is 0.5 for all the concrete samples. Table 4 summarizes the mixture proportion and slump obtained for control specimen and FRC. Mixture proportion and slump of HFC is shown in Table 5.

Table 4: Mixture Proportions and Fresh Concrete Properties for Control Specimen & FRC

Control Polypropylene Fiber Reinforced Concrete Nylon Fiber Reinforced Concrete Constituents (CC) P1 P2 P3 P4 N1 N2 N3 N4 OPC (kg/m3) 384 384 384 384 384 384 384 384 384 Sand (kg/m3) 711 711 711 711 711 711 711 711 711 Coarse aggregate (kg/m3) 1108 1108 1108 1108 1108 1108 1108 1108 1108 Water (kg/m3) 192 192 192 192 192 192 192 192 192 w/c ratio 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 PP by volume % – 0.1 0.3 0.5 0.7 – – – – Nylon by volume % – – – – – 0.1 0.3 0.5 0.7 Slump (mm) 75 73 72 70 67 72 70 68 65

[44] Concrete with Hybrid Polypropylene-Nylon Fibers

2.4 Mixing and Curing Coarse aggregate (CA) and fine aggregate (FA) were dry mixed in a concrete mixer for 1 minute. Cement was introduced in the dry mixture inside concrete mixer and was further dry mixed for 1 minute. After this, a specified amount of fiber as per Table 4 and Table 5 were distributed inside a concrete mixer with thorough mixing time of 3 minutes. Water was then added to the mix and was mixed for 3 minutes. The obtained concrete mix was poured in 150mm x 150mm x 150mm concrete cube mold, 150mm x 300mm cylinder mold and beam mold of dimensions 500m x 100mm x 100mm. The samples were demoted after 24 hours and was then placed in the curing tank for test age of 28 days and 90 days. Temperature of water inside the curing tank was maintained at 27 ºC ± 2 ºC.

Table 5: Mixture Proportions and Fresh Concrete Properties for of HFC Hybrid Fiber-reinforced Concrete Constituents 1H1 1H2 1H3 1H4 1H5 2H1 2H2 2H3 2H4 2H5 OPC (kg/m3) 384 384 384 384 384 384 384 384 384 384 Sand (kg/m3) 711 711 711 711 711 711 711 711 711 711 Coarse aggregate (kg/m3) 1108 1108 1108 1108 1108 1108 1108 1108 1108 1108 Water (kg/m3) 192 192 192 192 192 192 192 192 192 192 w/c ratio 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 PP by volume % 0.5 0.6 0.4 0.7 0.3 1 1.5 0.5 0.8 1.2 Nylon by volume % 0.5 0.4 0.6 0.3 0.7 1 0.5 1.5 1.2 0.8 Slump (mm) 69 70 66 69 65 65 59 55 57 60

2.5 Test Procedure 150mm cube specimens, 150mm x 300mm cylinder specimens and beam samples of dimensions 500m x 100mm x 100mm were prepared for all mix proportions specified in Table 4 and Table 5. Fresh concrete was cast into respective molds in three layers by compacting it with the help of a vibrating table and after 24hr, samples were removed from their molds. Afterward, all samples were cured under water for 28 days and 90 days. Compressive strength was performed in 28 and 90 days age 150mm cubes by applying a uniformly rated compressive load of 140 kg/cm² per minute until failure, splitting tensile strength was performed on 150mm x 300mm cylinder at a constant rate of 140 kg/cm2and flexural strength was determined using two-point loading method, applied to beam specimens with a uniform load rate of 400 kg/min.

3. RESULTS AND DISCUSSION Test results of control and the FRC are summarized in Table 6 and Table 7 present the test results of HFC. An average of three specimens has been considered as the strength value and is reported in Table 6.

Table 6: Mechanical Properties of Control Concrete, PP FRC Concrete and Nylon FRC Concrete Compressive Strength (MPa) Splitting Tensile Strength (MPa) Modulus of Rupture (MPa) Type 28 Days 90 Days 28 Days 90 Days 28 Days 90 Days CC 26.01 27.31 1.30 1.37 4.32 4.41 P1 32.18 32.28 1.78 1.98 4.51 4.59 P2 33.27 34.26 2.06 2.20 4.96 5.05 P3 34.53 35.39 1.90 1.99 5.1 5.18 P4 36.15 37.05 1.86 1.91 5.19 5.28 N1 29.47 30.94 1.92 2.10 4.9 4.96 Table 6 (Contd.)... [45] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

...Table 6 (Contd.)

N2 30.82 32.36 2.16 2.33 4.51 4.57 N3 31.93 32.72 2.04 2.13 5.49 5.61 N4 35.8 36.69 2.00 2.05 5.68 5.78

Table 7: Mechanical Properties of HFC Concrete Compressive Strength (MPa) Splitting Tensile Strength (MPa) Modulus of Rupture (MPa) Type 28 Days 90 Days 28 Days 90 Days 28 Days 90 Days 1H1 34.32 35.17 4.9 5.02 3.29 3.41 1H2 33.74 34.58 4.97 5.06 1.85 1.99 1H3 32.59 33.4 4.84 4.91 1.93 2.12 1H4 33.82 34.66 5.02 5.11 2.05 2.15 1H5 31.66 33.24 4.82 4.92 2.03 2.23 2H1 38.02 38.97 5.2 5.29 2.40 2.55 2H2 39.53 40.51 5.89 5.98 2.60 2.77 2H3 35.28 36.16 5.29 5.36 2.37 2.55 2H4 35.87 36.79 5.43 5.54 2.02 2.11 2H5 37.38 38.47 5.35 5.45 1.94 2.02

3.1 Slump Consistency of fresh concrete for all prepared samples for various portions as specified in Table 5 and 6 has been reported in the table itself. For control concrete, slump value obtained is 75mm and it is observed that the introduction of fibers reduces the slump. Lowest slump obtained is 55mm which correspond to HFC where 2% volume fraction of total for PP and nylon fiber is present. The reason of a reduction in slump may be due to formation of network structure in concrete because of high fiber content which may obstruct the flow of aggregates. Moreover, it’s likely possible that higher dosage of fiber may absorb more cement pastes resulting in an increase of the viscosity of the mixture and thereby contributing to slump loss [17].

3.2 Compressive Strength Figure 2 (a) and Figure 2 (b) compares the PP FRC and Nylon FRC with that of the controlled specimen at the age of 28 days and 90 days.

40 40 35 35

35 35 30 30

30 30 25 25 25 25 20 20 20 20 15 15 15 15 10 10 10 10 28d 90d28d 90d 5 5 28d 90d28d 90d 5 5 0 0 0 0

COMPRESSIVE STRENGTH (MPA) CCCOMPRESSIVE STRENGTH (MPA) P1CC P2 P1 P3 P2 P4 P3COMPRESSIVE STRENGTH (MPA) P4 CCCOMPRESSIVE STRENGTH (MPA) N1CC N2 N1 N3 N2 N4 N3 N4 CONCRETE TYPECONCRETE TYPE CONCRETE TYPECONCRETE TYPE

Fig. 2 (a): Compressive Strength Comparison of PP Fig. 2 (b): Compressive Strength Comparison of Nylon FRC in Various Proportions by Volume with CC FRC in Various Proportions by Volume with CC

[46] Concrete with Hybrid Polypropylene-Nylon Fibers It can be observed from both the graphs that increase of fiber proportion beyond 0.5% volume fraction decreases the compressive strength. The result of nylon fiber agrees with the finding by Hanif et al. [18]. The decrease in compressive strength may be because of the coarser microstructure with higher capillary porosity [19]. In case of HFC maximum compressive strength has been observed for sample with total 2% by volume fraction hybrid with 1.5% PP fiber and 0.5% nylon fiber as shown in Figure 3. Under axial loads, fibers limit the propagation of cracks and divert it. They bridge the crack and transfer the stress concentrated at crack to other stable hydrated cement matrix through fiber. Hybrid fibers (2H2) of PP and nylon fiber with 1.5% and 0.5% volume fraction may have shown this positive effect to increase the compressive strength. It can also be observed that 2H2 concrete has better compressive strength compared to other concrete type of HFC and FRC.

45 40 35 30 45 25 40 20 35 15 30 28d 90d 10 25 5 20 0 15 COMPRESSIVE STRENGTH (MPA) CC 1H1 1H2 1H3 1H428d 1H5 2H190d 2H2 2H3 2H4 2H5 10 CONCRETE TYPE 5 Fig. 3: Compressive Strength Comparison of HFC with Various Proportions in 0 Volume of PP and Nylon Fiber with CC 8.00 COMPRESSIVE STRENGTH (MPA) CC 1H1 1H2 1H3 1H4 1H5 2H1 2H2 2H3 2H4 2H5 7.00 CONCRETE TYPE 3.3 Splitting Tensile Strength and Flexural Strength 6.00 5.00 8.00 4.00 7.00 3.00 6.00 2.00 5.00 1.00 4.00

Splitting tensile strength Splitting tensile (MPa) 0.00 3.00 2.00 Concrete Type 1.00

Splitting tensile strength Splitting tensile (MPa) 0.00 28d 90d

Concrete Type

28d 90d

Fig. 4: Comparison of Split Tensile Strength with Different Concrete Types

[47] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Splitting tensile strength of concrete improves in HFC as can be observed from Figure 4. Sample 1H1 which comprise about 0.5% PP fiber and 0.5% by volume gives the maximum value compared to all other types. N4 sample which is an FRC comprising of only 0.7% nylon fiber has good splitting tensile strength compared to PP fiber. This may be due to the high tensile strength capacity of nylon fiber compared to PP fiber. However, from Figure 5, it can be interpreted that flexural tensile strength for total 1% volume fraction for HFC do not show much improvement compared to mono fiber. Beyond total 2% volume fraction for HFC, there is improvement in flexural tensile strength for 2H2 sample which comprise of PP and nylon fiber with 1.5% and 0.5% volume fraction. 2H2 sample also had better compressive strength compared to other concrete samples. Here also N4 FRC sample has the better flexural strength capacity compared to many of PP FRC and few of HFC.

Flexural (MPa) tensile strength 0

Concrete Type

28d 90d

Fig. 5: Comparison of Flexural Tensile Strength with Different Concrete Types

4. CONCLUSION Addition of hybrid polypropylene and nylon fiber has better compressive strength compared to FRC comprising of only nylon or polypropylene fiber. Usage of higher percentage of these mono fiber in concrete shows the declination in compressive strength. Beyond 0.5% by volume of the fiber fraction for both polypropylene and nylon decreases the compressive strength. Optimum percentage proportion for maximum compressive strength is observed for a total 2 % by volume fraction with 1.5% of polypropylene and 0.5 % nylon fiber. Flexural strength improvement in hybrid composition of fiber is effective for a total 2 % by volume fraction. Concrete sample with 1.5% of polypropylene and 0.5 % nylon fiber volume fraction gives maximum flexural strength compared to other hybrid proportions and mono fiber proportions. Nylon fiber with 0.7% by volume, has more tensile strength (both split as well as flexural tensile strength) capacity compared to polypropylene fiber. Split tensile strength is found to be more for hybrid fibers with proportion, 0.5% polypropylene and 0.5% nylon by volume fraction.

[48] Concrete with Hybrid Polypropylene-Nylon Fibers The main function for inclusion of fibers in concrete are to improve the tensile properties of concrete. Result of present study may aid in selecting proportion of synthetic fiber, polypropylene and nylon achieve desired compressive as well as tensile strength capacity.

REFERENCES [1] R.F. Zollo, “Fiber-reinforced concrete: an overview after 30 years of development,” Cement and Concrete Composites, vol. 19, pp. 107-122, 1997/01/01/ 1997. [2] O. Cengiz and L. Turanli, “Comparative evaluation of steel mesh, steel fibre and high-performance polypropylene fibre reinforced shotcrete in panel test,” Cement and Concrete Research, vol. 34, pp. 1357-1364, 2004/08/01/ 2004. [3] V. C. Li, H. Horii, P. Kabele, T. Kanda, and Y. M. Lim, “Repair and retrofit with engineered cementitious composites,” Engineering Fracture Mechanics, vol. 65, pp. 317-334, 2000/01/01/ 2000. [4] S. P. S. Editors and G. B. Batson, “SP-105: Fiber Reinforced Concrete Properties and Applications,” Special Publication, vol. 105, 12/1/1987. [5] M. Tavakoli, “Tensile and compressive strengths of polypropylene fiber reinforced concrete,” Special Publication, vol. 142, pp. 61-72, 1994. [6] P. S. Song, S. Hwang, and B. C. Sheu, “Strength properties of nylon- and polypropylene-fiber-reinforced concretes,” Cement and Concrete Research, vol. 35, pp. 1546-1550, 2005/08/01/ 2005. [7] C. Qian and P. Stroeven, “Fracture properties of concrete reinforced with steel–polypropylene hybrid fibres,” Cement and Concrete Composites, vol. 22, pp. 343-351, 2000. [8] L. Sorelli, A. Meda, and G. Plizzari, “Bending and uniaxial tensile tests on concrete reinforced with hybrid steel fibers,” Journal of materials in civil engineering, vol. 17, pp. 519-527, 2005. [9] N. Banthia and M. Sappakittipakorn, “Toughness enhancement in steel fiber reinforced concrete through fiber hybridization,” Cement and Concrete Research, vol. 37, pp. 1366-1372, 2007. [10] F. Köksal, O. Gencel, B. Unal, and M. Y. Durgun, “Durability properties of concrete reinforced with steel-polypropylene hybrid fibers,” Science and Engineering of Composite Materials, vol. 19, pp. 19-27, 2012. [11] K. H. Mo, K. K. Q. Yap, U. J. Alengaram, and M. Z. Jumaat, “The effect of steel fibres on the enhancement of flexural and compressive toughness and fracture characteristics of oil palm shell concrete,” Construction and Building Materials, vol. 55, pp. 20-28, 2014. [12] V. Afroughsabet and T. Ozbakkaloglu, “Mechanical and durability properties of high-strength concrete containing steel and polypropylene fibers,” Construction and building materials, vol. 94, pp. 73-82, 2015. [13] I. Sadrinejad, R. Madandoust, and M. M. Ranjbar, “The mechanical and durability properties of concrete containing hybrid synthetic fibers,” Construction and Building Materials, vol. 178, pp. 72-82, 2018/07/30/ 2018. [14] BIS, “IS 8112: Specification for 43 grade ordinary Portland cement,” in Bureau of Indian Standards, ed, 2013. [15] BIS, “IS 383: Specification for Coarse and Fine Aggregates From Natural Sources For Concrete,” in Bureau of Indian Standards, ed, 1970. [16] BIS, “IS 10262: Guidelines for concrete mix design proportioning,” in Bureau of Indian Standards, ed, 2009. [17] B. Chen and J. Liu, “Contribution of hybrid fibers on the properties of the high-strength lightweight concrete having good workability,” Cement and Concrete Research, vol. 35, pp. 913-917, 2005/05/01/ 2005. [18] I. Hanif, M. Syuhaili, M. Hasmori, and S. Shahmi, “Effect of nylon fiber on mechanical properties of cement based mortar,” in Materials Science and Engineering Conference Series, 2017, p. 012080. [19] V. C. Li, “A simplified micromechanical model of compressive strength of fiber-reinforced cementitious composites,” Cement and Concrete Composites, vol. 14, pp. 131-141, 1992.

[49] Measurement of Construction Productivity by using Situational Based Modelling

Prasanna Honkalas1 and Vikas Varekar2 1M.Tech. Student, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Assistant Professor, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected]

ABSTRACT Construction is huge business tied to the development of different industries each in backward and forward relationships. It makes a significant contribution to the nation’s economy and provides employment to large number of people. The use of new technologies and deployment of project management strategies has made it possible to undertake projects of mega scale. In its path of advancement, the industry faces number of challenges. To make things smoother the measurement of performance is important. In order to ensure the performance of a project, past researchers have analyzed some measurable key parameters such as cost, safety, construction productivity, and quality. Amongst all of them, construction productivity is one of the most reliable parameters of project performance because site productivity losses range from 40% - 60%. Site operations are very complex, and they involve complicated relationship amongst various activities, risks, uncertainties and affecting situations which directly impacts on performance. By tackling the situations affecting on site productivity could definitely improve the performance. The paper discusses about technique known as Situational based modelling. The tool used directly investigates and analyses these affecting situations to predict root cause of productivity loss. The methodology adopted to conduct the study is to collect the data through a direct observation method. The construction activity is observed for 8 to 9 hours per day till completion of that activity. The simulation results from simulation not only able to predict productivity closely to the actual productivity observed at construction sites, but also provide recommendations to improve productivity. Keyword: Productivity, Situational Based Modelling, Situations

1. INTRODUCTION The construction industry has a major importance within the economic, social, and infrastructure development of any country. Any positive modification in implementation level of construction industry can provides a vital result towards a country’s Gross Domestic Product (GDP). Therefore, the expansion within the construction sector includes a vital impact on the economy of the nation. In India long run GDP growth from middle Nineteen Nineties has currently stepped up to 6.5%. According to construction industry development council India in year 2006–07 construction labour force rate of growth is increased by 1% (Indian Construction Industry 2006–07). However still the construction industry faced variety of problems like lack of skilled workforce, non-availability of land within town limits, technology adoption, project complexness, government policies, environmental sustainability, and natural hazards. The downward trend of productivity has been studied by various researchers for several years. however, reports show site productivity losses are around 40%–60% [4]. Construction operations are complicated in nature; they involve complicated relationships among numerous activities. [4]. It’s difficult to draw a solution based on the investigation of just one or two factors. As a result of these factors that affect productivity are associated with difficult relationships or the activities themselves.

[50] Measurement of Construction Productivity by using Situational Based Modelling to enhance productivity, project managers and engineers initial need to understand the behaviour of those factors. For these reasons, this paper represents a modelling technique, called situation-based modelling. This modelling technique can predict productivity by analysing the interaction of the situations that have an effect on productivity and their individual and combined impact on productivity.

2. BACKGROUND The term Productivity has various definitions. In this paper, productivity represents the unit of output produced by one unit of input because this paper focuses on site labour productivity. Productivity improvement relies on the understanding of the work process and the impact of those factors, obstacles, or situations on productivity. It is proven by literature that, as region changes productivity of work changes (loss or gain). It varies the factors affecting on work and occurring situations which impacts on progress of work. It also recognized that efficiencies of manpower, working methods availability of resources differs from place to place. Over the history of few years, various modelling concepts, originating from the manufacturing industry, have been applied in the construction area. Models by Walker (1985), Sanvido (1984), Chung (1989), Howell and Koskela (2000), Kartam et al. (1997) and Ruwanpura et al. (2001) all aimed to improve construction operations either from the perspective of the construction environment (which is system modelling), or the construction process (which is process modelling). However, these models have paid less attention to root cause of productivity loss. Situation based model proved to overcomes this drawback. There is no modelling technique capable of modelling a construction operation taking into account the triggering situations that cause productivity loss, delays, or other unsatisfactory outcomes. Only the situation model can address this aspect [1]. For instance, a plastering work will not succeed without availability of human resources, material and equipment. The construction method adopted is standardized. Thus, it is inappropriate to define the process without addressing the seemingly insignificant situations related to this process. The reason for applying the situation model in construction: 1. Existing modelling techniques not effective to find out various situation related to construction operations. However, this study shows that how the model is more realistic than input based statistical distributions. 2. The concept of situation model considers the risk factor that can affect other situations. Main focus of this paper is to provide the tool that engineers and project managers can use to predict productivity for building construction project. 1. To apply situation model to identify and quantify the productivity loss. 2. To explain the data collection from actual construction operations to identify various situations. 3. To provide recommendations for productivity improvement.

3. MONITORING OF CONSTRUCTION WORK The data collection for this study was done in two phases (1) Identification of situations (2) analysis of the situation and productivity. For identification of situation the observations are taken using direct observation method. Direct observation is one of the continuous observation methods. A researcher observes workers’ activities throughout the workday. Productive (direct work and supportive work) and non-productive activities are easily and accurately identified as the input times recorded to the nearest minute. But the main advantage of this method is, (1) data collected is accurate and precise. (2) The length and pattern of time of each work task can be collected.

[51] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) The method is generally considered as tedious and time wasting. One technique to increase this method’s efficiency is to highlight only the non-productive instances provided that the workers spend more time in productive activities than non-productive activities. Another criticism of this method is that the observer’s presence may disturb workers (Noor 1998). Hence it is recommended that the observer could locate him or she in a suitable vantage point where there is a full view of all workers but at the same time does not interfere with the operation’s progress. The only disadvantages of the direct observation method is, the observer is restricted in the number of workers he or she can view simultaneously. It suggests that a crew of five workers is the maximum crew size one observer can manage. A crew size that exceeds this number does not allow the observer to pay sufficient attention to each crewmember (Noor 1998). The observations are taken for the internal plastering work main reason for selection this activity is (1) The working method of plastering is substantially standardized in industry. (2) Labour intensive work. (3) There are various factors influencing the timely completion of this work. The masons and their helpers working time, non-working time and output were recorded for working hours (8 to 9 hours) per day till the completion this activity. This pilot study surveyed a construction sites located at southern regions of Mumbai city and 44 factors affecting which are categorised according to 5 different characteristics. The most significant factors were further categorized into nine clusters as shown in Table 1. These nine clusters and their related factors were used to identify the situations for site operations. The observation was done for month of April 2019. While observing following three assumptions are considered: 1. Modelling the structural operation of high-rise building. 2. The crew size of an activity does not change once the operations start. 3. The Situation of one activity cannot link to the Situations of another activity.

4. CONCEPTUAL FRAMEWORK OF SITUATION MODEL IN CONSTRUCTION The conceptual framework of this study is the relationship between situations and productivity. In construction operations, productivity is calculated by measuring the amount of output produced by a given number of work hours. As stated above, the number of work hours are divided into working time and non-working time; only the working time can produce output. The principle of this study is that situations are the only causes of productivity loss. Any risks, events, or accidents that cause productivity loss are regarded as situations. Because situations are the only causes of productivity loss, the role of situations is to affect the amount of both working time and output and also related situations. The conceptual frame work of study is as shown in figure below

Fig. 1: Conceptual Framework

Source: Choy and Ruwanpura 2005, Page no. 6 [52] Measurement of Construction Productivity by using Situational Based Modelling The Three major relationships of the model: (1) Relationship between Situations and Working Time, (2) Relationship between Situations and Output, (3) Relationship between Working Time and Output [1]. The following sections explain each relationship in mathematical terms.

4.1 Relationship between Situations and Working Hours Work Hours, or total time (TT), represent the total hours the contractor is required to pay for the laborers work. However, if the working hours or paid hours are eight hours a day, the laborers very often do not perform eight hours’ direct work. The actual working time (WT) is in a range of 40% to 60%; the rest is non-working time (NWT), or time of not performing direct work: Workhours (TT) = Working Time (WT) + Non-Working Time (NWT) (1)

Workhours (TT) =Working Time (WT) + ST (2) OR

Workhours (TT) = Working Time (WT) + (ST1,ST2,…., STn) (3)

Where ST represents the set of Situations in the form of times, which is equivalent to

Non-Working Time (NWT) = ST (4) Above equations 2 and 3 represent the first role of Situations, which is the determinant of non-working time. The equations show that the non-working time of construction operations are the result of situations occurring (Choy and Ruwanpura 2006).

4.2 Relationship between Situations, Working Time and Output Working hours (TT) are the total time for which the contractor pays the laborers, but these hours do not represent the amount of time contributed to the output. The time in which the laborers perform direct work is the Working Time (WT). A simple relationship between working time and output is as follows

WT Output However, past studies have proven this relationship is insufficient, as there are numerous unexpected events, risk factors, or accidents that occur during the course of construction operations that affect the production rate even if the workers are working. It is obvious that non- working time definitely generates a zero output but working time does not guarantee a 100% efficiency to generate output while there are some factors affecting this efficiency. Thomas (1991) who found that there was little correlation between outputs and the amount of time spent on direct work. The production rate of working time varies from different factors. These other factors are regarded as Situations that affect the performance, or output, during the Working Time. Some examples of these Situations are lack of materials, waiting for preceding work to be done by another crew, or a weather factor. A modified model to represent this relationship is

WT * p = Output (5) Where, p is the efficiency of the magnitude of Situations. In an ideal world, the value of p is the maximum possible according to the given technology. The relationship among Working Time, Situations, and Output is

WT * Sm = Output (6) OR

WT * (Sm1, Sm2, ..., Smn) = Output (7)

Where, Sm represents the set of the Situation’s magnitudes. From definition of productivity, the equation of productivity can be derived as [53] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

WT*Sm Productivity P = (8) (8) Work Hours ሺ ሻ Above equation 8, represent the second role of Situations, which is the efficiency of working time to generate output (Choy and Ruwanpura 2006).

WT*(Sm1,sm2,……Smn) 4.3 The Roles of Situations=Productivity in Productivity (9) WT+(St1,St2,……Stn) Above two equation shows fundamental role in process. The first role is that they affect the amount of Working Time given a Total Time, which provides a ratio of working time as opposed to non-working time.

Some past productivity studies stop at this point and take this ratio as an indicator of productivity, but this study proceeds to the second role of Situations, which is the efficiency of working time to generate output. WT*Sm After the outputProductivity is produced, P = the value of productivity can be achieved by(8) dividing the Input, which is the Total Time or Work Hours. Work Hours ሺ ሻ Work Hours combining all these elements from equation 3,7 and 8, the conceptual framework of this study is illustrated in equation below:

WT*(Sm1,sm2,……Smn) =Productivity (9) (9) WT+(St1,St2,……Stn)

Where, WT x (S , S ,.…, S ) represents the Output, and WT + (S , S , …, S ) represents the Input, m1 m2 mn t1 t2 tn which shapes the original definitions of Productivity [2].

5. SITUATIONS One important task of this study was to find out the situations on the basis of literature survey. The situations represent the actual events and incidents that occur on site. Table 1 illustrates the definition and related factor of each situation type. The observation categories represent the non-working time for plastering crew assigned for internal plastering work. The literature review and the pilot study found factors or clusters that covered a wide range of circumstances. However, a situation model requires that situations be defined with specific details. Accordingly, because the model assesses the site operations and site productivity, the situations are the actual events, accidents, or risks occurring on the site.

Table 1: Observation Categories of Non-working for Plastering Crew Sr. No. Situation Description 1 Extra Timing Represents late start and early finish of work. This category includes all the time which are extended non-working time before and after official breaks. 2 Travelling workers required to travel to new working area to perform work 3 Weather day to day weather condition on site (cold, humid, rainy, hot). This situation is influenced due to weather observation category and its relative working time. 4 Crowded area working area is crowded with workers. Some performing direct work and some performing supporting activity. This situation is influenced due to watching irrelevant, moving material observation categories 5 Instruction workers either waiting for instruction or being instructed by supervisor. This category is influenced due to instruction observation category and its relative working time. 6 Interruption workers performing irrelevant or another crew’s work as per the orders of supervisor or instructor.

Table 1 (Contd.)...

[54] Measurement of Construction Productivity by using Situational Based Modelling

...Table 1 (Contd.)

Sr. No. Situation Description 7 Material workers are waiting for, searching for, moving material or delay in dismantling reusable material. This situation is occurring due to idle, inspection, measure, moving, mixing and waiting for availability of material. 8 Precedent workers waiting for completion of precedent work by another crew so they can perform their work. This situation is influenced due to idle, inspection, irrelevant observation categories. 9 Saturated area working area is nearly finished but new work is not yet assigned to crew. Less amount of work is needed to perform. This situation occurs due to idle, irrelevant, moving material, leave, inspection, watching.

Source: E. Choy and J. Ruwanpura 2006 There are two basic concepts for situation: non-working time, situation’s magnitude. The non-working time is recorded for each observation category and rounded to minutes during observations. Non-working time is used to calculating the magnitude of situations. A situation illustrated in Table 2 are fully or partially depend on observation categories. When situation is fully dependant, all the non-working time for this observation category are regarded as relevant to this situation. when situation is partially dependant, the field comments specify which non-working time period are relevant to situation. The magnitude of situation represents the degree of severity. magnitude is measured by dividing the total amount of working time in working hours by the time related to situation in that period. Higher magnitude shows that the situation exists to greater extent. The equation for magnitude is

Ob 1 + Ob 2 + …+ Ob n + relevant WT Magnitude = (10) (10) Total Time ሺ ሻ ሺ ሻ ሺ ሻ

6. DEVELOPMENT OF SITUATION-BASED SIMULATION MODEL TEMPLATE Simulation is very effective tool for problem solving and decision making. The main purpose of simulation model is problem solving.

Table 2: Observation Categories of Non-working for Plastering Crew Sr. No. Observation Categories Description 1 Extra Breaks Represents late start and early finish of work. This category includes all the time which are extended non-working time before and after official breaks. 2 Waiting Material Represents non-working time for availability of material. 3 Moving Material Represents the time in which the worker is moving materials from one location to another location, but the materials are not used. 4 Mixing Material Represents the time in which worker is preparing freshly mixed mortar 5 Way for work Represents the time in which the worker is searching for or customizing materials for direct use. 6 Equipment Represents the time in which the worker is looking for, equipping, setting, or waiting for tools, equipment, or power supply. 7 Watching Represents the non-working time in which the worker is watching another worker performing work. Applies to more than one worker working together. 8 Precedents Represents the time in which the worker cannot perform work because the worker is waiting for completion of brick work, pointing work, surface preparation work, surface curing or when inspection work is being done by other crews. 9 Instructions Represents the non-working time in which the worker is waiting for instructions or being instructed by a foreman or supervisor.

Table 2 (Contd.)...

[55] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

...Table 2 (Contd.)

Sr. No. Observation Categories Description 10 Travel Represents the time in which the worker is traveling from a working area to another working area. 11 Interruption Represents the time period in which the worker is directed by the foreman or supervisor to perform work that is not regarded as relevant work. 12 Socialize Socializing or chatting time. 13 Inspection Represents the time in which the worker is checking the alignment and level, which results no direct output is produced. 14 Measure Represents the time in which the worker is measuring materials & level of applied plaster. 15 Safety Time relating to safety meetings or safety instructions given by the safety coordinator. 16 Leave Represents the time in which the worker leaves the working area without a valid reason. 17 Irrelevant Represents the time in which the worker is working on non-value-added activities. Such as cleaning, packing irrelevant material. But in this category foreman’s or supervisors’ instructions not involved. 18 Discuss Represents the time in which the workers are discussing the construction plans and working plan. 19 Idle Represents the non-working time that does not fall into any categories of this list.

Source: E. Choy and J. Ruwanpura 2006 Following is the observation table for the data collected from construction site. The time is recorded for each observation category to situations nearest minute.

Table 3: Observation Data Collected for Construction Site in Southern Mumbai Region

Observation category Extra Breaks Waiting Material Moving Material Mixing Material for Work Way Equipment Watching Precedents Instructions Travel Interruption Socialize Inspection Measure Safety Leave Irrelevant Idle Working Working Days Date Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. Min. 1 08-Apr 0 0 0 0 0 0 0 360 0 0 0 0 0 0 0 0 0 0 2 09-Apr 0 0 0 0 0 0 0 360 0 0 0 0 0 0 0 0 0 0 3 10-Apr 30 0 60 0 0 0 60 0 20 60 0 30 0 0 5 120 30 15 4 11-Apr 40 0 30 20 10 0 20 10 10 20 25 20 10 5 5 15 20 10 5 12-Apr 35 10 15 25 5 5 10 5 5 15 5 20 10 5 0 10 30 5 6 13-Apr 60 5 10 20 5 0 15 5 10 15 0 15 15 10 0 15 20 5 7 15-Apr 60 0 10 20 5 0 5 10 10 15 10 15 15 10 5 15 15 15 8 16-Apr 45 0 20 25 5 0 5 5 5 10 0 15 10 5 0 10 10 20 9 17-Apr 35 10 15 20 5 5 10 0 5 15 10 20 15 10 0 20 15 15 10 18-Apr 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 360 0 0 11 19-Apr 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 360 0 0 12 20-Apr 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 360 0 0 13 22-Apr 90 10 15 25 0 0 10 5 5 20 0 5 5 0 0 10 10 5 14 23-Apr 60 0 5 20 0 0 15 10 5 15 0 15 5 5 5 10 15 5

Table 3 (Contd.)... [56] Measurement of Construction Productivity by using Situational Based Modelling

...Table 3 (Contd.)

15 24-Apr 60 10 5 20 0 0 10 0 5 20 0 20 15 5 5 15 20 10 16 25-Apr 30 0 15 30 5 10 5 5 5 10 15 15 10 5 0 5 30 10 17 26-Apr 150 0 10 15 0 0 15 0 10 10 30 30 0 0 0 20 30 15 18 27-Apr 30 0 10 20 5 0 20 0 10 20 15 20 5 10 5 10 20 20 19 30-Apr 35 0 5 15 5 0 10 5 10 15 0 10 10 0 5 5 15 5

7. RESULTS AND DISCUSSION Following table represent the accumulated situation’s magnitude.

Table 4: Comparison Chart of Situations No. of No. of Highest Average Region Work Type Situations Observed Presence Magnitude Magnitude Frequency Days Days (%) (%) Extra Breaks 19 14 16.667 11.111 73.68 Travelling 19 14 20.833 11.404 73.68 Weather 19 19 0 0.000 0 Construction Site at Crowded area 19 14 25 7.164 73.68 Internal Southern Instruction 19 14 5.556 1.681 73.68 Plastering Mumbai Interruption 19 14 25 7.895 73.68 Region Material 19 14 22.223 13.085 73.68 Precedent 19 16 100 19.591 84.21 Saturated area 19 17 79.167 34.430 89.47 Above table shows how Situations are identified and describes the quantification methodology used for this study. The Situation identification process is based on a literature review. Nine situation types are identified in total. According to the figures included in this chapter, different Situations have different magnitudes. Some Situations occur almost every day while others occur rarely. Some Situations affect up to 100% of the work hours; other situations have only a slight effect. The most influential Situations are those having both high frequency and average magnitudes because these show that the Situation occurs very often, and the impact of each occurrence is high.

Table 5: Value of Critical Performances Expected Average Productivity Productivity NWT TT Output Productivity WT (hr) Completion Crew Accumulated Required (hr) (hr) (Sq. M) Loss Duration (hr) Size (Sq./hr) (Sq.M/hr) 66.583 85.417 152 114 6 4190 27.5658 36.7544 9.1886 Benchmark data is the actual data collected for the finishing work of the High-rise residential building project. The aggregate values of the critical performances are illustrated in Table No 5.

8. SUMMARY AND CONCLUSION From observation taken using direct observation method, field comment shows that the workers strike, and unavailability makes huge impact on schedule of project. Other situations have similar kind of impact on project. The weathering condition do not make any effect on performance. It shows that the precedent work still not completed but the new workers crew had given a succeeding work. The loss of time occurred due to the workers getting socialized, they started watching another crews work, worker cannot perform [57] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) work because the worker is waiting for completion of brick work, pointing work, surface preparation work, surface curing or when inspection work is being done by other crews. Moreover, their time also wasted on leaving work without reason, and doing irrelevant work. To mitigate this effect the project manager or site engineers to give the correct solution on basis of their own experience and expert opinion. They should timely track the record of work performance without compromising the quality of work. This special purpose simulation tool for building construction operations, is a useful tool for the construction industry. This model allows users to build the models based on the interactions of various situations and work types. The models can predict the situations’ impact individual or combined and the productivity. This information can help the user to find the most critical situation or situations for productivity improvement. The examples given in the paper show the situations’ impact on productivity. The model outputs explain the logic behind situations. The example given above shows that mitigating situations occurance is a good strategy for productivity improvement. Because of this feature, the users can easily discover the impact of each situation based on the modelling results.simulation shows the situation model’s flexibility and how it can thus be applied in other academic and industrial areas in the future.

ACKNOWLEDGEMENT The authors thank Veermata Jijabai Technological Institute, Matunga, Mumbai, 400019, for providing infrastructural facilities and support for successful completion of their research work.

REFERENCES [1] Choy, E. and Ruwanpura, J.Y., 2005. Modeling Site Construction Productivity using Situation based Simulation. Selected for the Canadian Journal of Civil Engineering – special issue in Construction, NRC Press Canada. [2] Dozzi, S.P., AbouRizk, S.M., 1993. Productivity in Construction., Institute for Research in Construction, National Research Council, Ottawa, Ontario, Canada. [3] Choy, E., Ruwanpura, J.Y., 2006. Situation Based Modeling for Construction Productivity. Construction Research Congress 2005. [4] Hajjar, D., AbouRizk, S. M., 2000. Application Framework for Development of Simulation Tools. Journal of Computing in Civil Engineering, Jul 2000, Vol. 14 no. 3, pp. 160-167. [5] Lewis, C. M., 1991. Visualization and Situations. Situation Theory and Its Applications, Vol. 2, pp. 553-580. [6] Nakashima, H., Tutiya, S. 1991. Inferring in a Situation about Situations. Situation Theory and Its Applications, Vol. 2, pp. 215-228. [7] Noor, I. 1998. Measuring construction labour productivity by daily visits. Transactions of AACE International, Morgantown 1998, 16-21 [8] Ruwanpura, J.Y., AbouRizk, S.M., Er, K.C., Fernando, S., 2001. Special purpose simulation templates for tunnel construction operations. Canadian Journal of Civil Engineering, CSCE, 2001, 25,3 1–16. [9] Thomas, H. R., 1991. Labour Productivity and Work Sampling: The Bottom Line. Journal of Construction Engineering and Management, Sept 1991, Vol. 117 No. 3, pp. 423-444. [10] Thomas, H.R., Daily, J., 1983. Crew Performance Measurement Via Activity Sampling. Journal of Construction Engineering and Management. Sept 1983, Vol. 109 No. 3, pp. 263-277. [11] Thomas, H. R., Guevara, J. M., Gustenhoven C T., 1984. Improving Productivity Estimates by Work Sampling. Journal of Construction Engineering and Management, Apr 1984, Vol. 110 No. 2, pp. 178-188. [12] Thomas, H. R., Maloney, W. F., Horner, R. M. W., 1990. Modelling Construction Labour Productivity. Journal of Construction Engineering and Management, Dec 1990, Vol. 116 No. 4, pp. 705-726. [13] Thomas, H. R., Riley, D. R., Sanvido, V. E., 1999. Loss of Labour Productivity due to Delivery Methods and Weather. Journal of Construction Engineering and Management, Jan 1999, Vol. 125 No. 1, pp. 39-46 [14] Tin, E., Akman, V., 1994. Computational Situation Theory. ACM Sigari Bulletin 5,4. [15] Zalta, E. N. 1991. A Theory of Situations. Situation Theory and Its Applications, Vol. 2, pp. 81-111. [16] Zwaan, R., Langston, M. C, Graesser, A., 1995. The construction of situation models in narrative comprehension: an event- indexing model. Psychological Science, 6, pp. 292–297.

[58] Performance Characteristics of Ceramic Waste Concrete with Fly Ash and Granite Powder as Filler

Nikhil Gharat1 and Vikas Varekar2 1M.Tech. Student, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Assistant Professor, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected]

ABSTRACT Concrete is a construction material used by engineers for than two centuries now. It is one of the most frequently used building materials. It is been stated by earlier researchers that the usage of concrete is twice that of wood, plastic, steel and aluminum together. But there are disadvantages of concrete as well. A major component of concrete is cement, which has its own environmental and social impacts. Cement in concrete can cause health concerns due to toxicity. So, there is a need to find an alternative for cement in concrete. Fly ash and Granite powder are the materials used previously as a partial replacement of cement. Granite powder from the stone industry and fly ash from thermal power plants are the waste materials that are produced in huge quantity. These materials cause adverse effect on environment and health of people living in surroundings of these industries. This paper studies the possible use of theses waste materials as a partial replacement of cement as filler in ceramic waste concrete. Compressive strength of concrete by using these waste materials is studied with the experimental analysis. Standard concrete mix was compared with 12 prepared mixes for the compression strength parameter. The results suggest that fly ash and granite powder have very good potential for their use as filler in concrete. Among the three wastes used, fly ash show most promising effects on concrete and is seen to be economical also. Keywords: Fly Ash, Ceramic Waste, Granite Powder, Rigid Pavement Design, Sustainable Concrete

1. INTRODUCTION Waste materials from industries and the disposal of them is a big problem in every part of the world today. Waste materials are mainly formed from construction and demolition works and service industries, municipal solid wastes, manufacturing processes. Today there has been plenty of awareness regarding the environment and it has contributed to the concerns related with disposal of these generated wastes. Most concerning of all is solid waste management in world and there’s not enough area for land filling and because of its increasing cost; waste utilization is becoming a very useful alternative to disposal. There are several researchers that are carrying out research associated with this subject and plenty of researchers are focusing on concrete related topics because it is a very big problem nowadays. This will result in use of manually manufactured materials instead of using natural materials available and that are depleting these days, which will make concrete more economical and therefore the problem of waste disposal will be resolved. When the Ceramic waste is used as coarse aggregate in concrete, it is called as ceramic waste aggregate concrete. Nowadays around 30% of the ceramics are wasted and that they are not being recycled [1]. Ceramic wastes are the wastes obtained from the industries that manufacture tiles, sanitary products. Waste ceramic materials are very cheap alternative to be utilized in concrete. An outsized part of this industry that is approximately 2% and varies with countries and industries accordingly is thrown as scrap is a larger contributor of industrial waste.

[59] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) In concrete, if the cement content is less, then it leads to more voids in concrete. This results in reduction in strength and durability of concrete. Similarly, if the cement content is more, then it results in more shrinkage of concrete and less strength and durability. Granite powder can be obtained from crushing of stones of granite and it is available in industries where polishing of these stones is done. The powder is to be treated, collected and stored properly otherwise is hazardous to health and is easily spread through air. It is determined that the people living close to granite mills are more likely to have lung diseases. By using granite powder in concrete, the health hazards of these industrial wastes can be minimized. Fly ash is produced during combustion of coal while using for production of energy, that is an industrial by- product and is a very hazardous environmental waste product [5]. As fly ash causes several environmental issues, there has been a lot of research going on, on the utilization of fly ash in different industries. This study deals with reviewing and analyzing the usage of different quantity of Ceramic waste, fly ash and Granite powder in concrete and its effect on workability, compressive strength and durability of concrete of various mixes.

2. MATERIALS AND METHODS

2.1 Methods Standard M25 grade concrete (IS 456:2000) along with 12 different mixes of varying proportion of Ceramic waste, Fly ash, Granite powder were cast to review the impact of these materials in varied proportion on the strength of concrete. The mix proportion used for all the mixes was same and the mixes were divided according to the proportion of waste materials utilized in each mix. The strength of standard mix was expected to be 25 mPa to 30 mPa on 28th day. To design the mixes, fly ash and Granite powder were used as a partial replacement to cement and as a filler material whereas Ceramic waste is used as a partial replacement of coarse aggregates. The proportion by which fly ash is replaced varies in 10% to 20% while Granite powder is replaced in 5% and 10% for different mixes. The replacement of Ceramic waste for coarse aggregate is in the percentage 20%, 30% and 40%. Maximum water: cement ratio used for all the mixes including standard mix is 0.45. The cement, fine aggregates, coarse aggregates and water used for standard mix and other designed mixes are same.

Table 1: Proportions of Waste Materials Used in Concrete in Different Mixes Mix Ceramic Waste (%) Fly Ash (%) Granite Powder (%) M30 00 00 00 Mix 1 20 10 5 Mix 2 20 10 10 Mix 3 30 10 5 Mix 4 30 10 10 Mix 5 40 10 5 Mix 6 40 10 10 Mix 7 20 20 5 Mix 8 20 20 10 Mix 9 30 20 5 Mix 10 30 20 10 Mix 11 40 20 5 Mix 12 40 20 10

[60] Performance Characteristics of Ceramic Waste Concrete with Fly Ash and Granite Powder as Filler

Minimum cement content (as per IS 456:2000) is maintained to be 320 kg/m2. The constituents of the concrete mixtures were calculated on the basis of pilot readings mixes, conventional concrete mix design. The final mixtures used for the calculations properties of concrete in detail are given in Table 1. The proportions were chosen based on the previous studies done on Ceramic waste, Fly ash and Granite powder. The mix proportions are summarised in the Table 1.

2.2 Materials

2.2.1 Cement For the experimental work of the study, the main binding material used is Ordinary portland cement of grade 53 (as per BIS specification IS:12269-1987). The properties of the cement obtained from the manufacturer are as follows-specific surface area (SSA) was 330 m2/kg, specific gravity (SG) equal to 3.15.

2.2.2 Aggregates Natural crushed aggregate as fine aggregate as well as coarse aggregates was used. The maximum size of aggregates used was 20 mm for coarse aggregate and 4.75 mm for fine aggregates, The properties of aggregates are as follows-specific gravity is 2.60 and absorption percentage of the used coarse aggregates 1.5%.

2.2.3 Waste Materials The materials used for replacement of cement are granite powder and fly ash. The specific gravity of fly ash was 2.2 gm/cm3 as per the supplier. Total percentage of waste material used (Fly ash and Granite powder) to partially replace cement as a binding material varied from 10% to 30%. Granite powder used was the same throughout the span of work and was collected from the granite rock processing industry. Fly ash used for the work was obtained from a single source as well. Ceramic waste obtained was taken from a single supply throughout the study. The source of ceramic waste was a storage facility used for the ceramic tiles. The pre processing for the use of ceramic waste in the concrete casting was to crush the ceramic waste in desired sizes and to carry out sieving of the obtained crushed material. Total percentage of waste material (Ceramic waste) used to partially replace coarse aggregate varied between 20% to 40% decided based on previous studies.

2.3 Testing Some tests were conducted to analyse the effects of using waste materials to partially replace cement and aggregates. The compressive strength was tested on 150 × 150 × 150-mm cubes at three test ages (3, 7 and 28 days) to evaluate the strength development in the mixtures designed and standard mixture. At every time of curing, three concrete specimens were tested. There are other few parameters for obtaining strength of the concrete but the evaluation of compressive strength of hardened concrete are sufficient to study the pattern of change in properties. So, these tests were conducted.

3. RESULTS AND DISCUSSION

3.1 Compressive Strength Test Fig. 1, Fig. 2, Fig. 3 shows the development of compressive strength of standard mix design. The strength varies as per the percentage of waste material varies, and the strength increases as the time passes i.e. strength increases in order 3 days, 7 days and 28 days. This can be observed due to properties of cement [61] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) to gain strength. The compressive strength test was done at 3 days,7 days and 28 days. The results indicate that the standard mix used shows better results in early stage of curing. But at 7 days and 28 days tests, some of the prepared mixes show better results than the standard mix.

3 Days3 Days 7 Days7 Days 16 16 19 19 14 14 3 Days 18 18 7 Days 12 12 1610 10 1917 17 148 8 1816 16 12 6 6 1715 15 104 4 82 2 1614 14 60 0 1513 13 4 2 14 M25 M25 M25 M25 Mix1 Mix2 Mix1 Mix3 Mix2 Mix4 Mix3 Mix5 Mix4 Mix6 Mix5 Mix7 Mix6 Mix8 Mix7 Mix9 Mix8 Mix9 13 Mix1 Mix2 Mix1 Mix3 Mix2 Mix4 Mix3 Mix5 Mix4 Mix6 Mix5 Mix7 Mix6 Mix8 Mix7 Mix9 Mix8 Mix9 0 10 Mix 11 Mix 10 Mix 12 Mix 11 Mix 12 Mix 10 Mix 11 Mix 10 Mix 12 Mix 11 Mix 12 Mix Compressive Strength mPa Strength Compressive Compressive Strength mPa Strength Compressive Compressive Strength mPa Strength Compressive Compressive Strength mPa Strength Compressive ConcreteConcrete Mix Mix ConcreteConcrete Mix Mix M25 M25 Mix1 Mix2 Mix3 Mix4 Mix5 Mix6 Mix7 Mix8 Mix9 Mix1 Mix2 Mix3 Mix4 Mix5 Mix6 Mix7 Mix8 Mix9

Mix 10 Mix 11 Mix 12 Mix 10 Mix 11 Mix 12 Mix Compressive Strength mPa Strength Compressive Compressive Strength mPa Strength Compressive Fig. 1: CompressiveConcrete Strength Test Mix Results (3 Days) of Fig. 2: CompressiveConcrete Strength Mix Test Results (7 Days) of Prepared Concrete Mixes using Ceramic Waste, Prepared Concrete Mixes using Ceramic Waste, Fly Ash and Granite Powder 28 Days28 Days Fly Ash and Granite Powder 36 36 35 35 28 Days 34 34 3633 33 3532 32 3431 31 3330 30 3229 29 31 30 M25 M25 Mix1 Mix2 Mix1 Mix3 Mix2 Mix4 Mix3 Mix5 Mix4 Mix6 Mix5 Mix7 Mix6 Mix8 Mix7 Mix9 Mix8 Mix9

29 10 Mix 11 Mix 10 Mix 12 Mix 11 Mix 12 Mix

Compressive strength mPa strength Compressive mPa strength Compressive ConcreteConcrete Mix Mix M25 Mix1 Mix2 Mix3 Mix4 Mix5 Mix6 Mix7 Mix8 Mix9

Mix 10 Mix 11 Mix 12 Mix

Compressive strength mPa strength Compressive Concrete Mix

Fig. 3: Compressive Strength Test Results (28 Days) of Prepared Concrete Mixes using Ceramic Waste, Fly Ash and Granite Powder

4. CONCLUSIONS Results of compressive strength test on concrete mixes with fly ash, ceramic waste and granite powder are presented and compared in this paper. The effect of using waste materials as filler material is explained. From the prepared mixes, It is found that the concrete when used with waste materials does not gain strength in early stage. The optimum results were obtained when the fly ash in concrete was about 20%. When granite powder was used more than 5% then it shown adverse effect on the strength. Replacement of waste materials in concrete up to some limits show significantly positive results. And it can be concluded that, ●● Standard mix concrete tends to gain more early days strength as compared to the concrete with waste materials used in it. [62] Performance Characteristics of Ceramic Waste Concrete with Fly Ash and Granite Powder as Filler ●● Later days strength of some prepared mixes is more than the standard mix but some mixes still show poor performance as compared to standard mix concrete. So, in the construction industry it is important to increase the confidence of engineers to use these waste materials. This can release the burden over construction industry in overall cost perspective and also over the authorities to demolish and management of these wastes.

ACKNOWLEDGEMENTS The authors thank Veermata Jijabai Technological Institute, Matunga, Mumbai, 400019, for providing infrastructural facilities and support for successful completion of their research work.

REFERENCES [1] Bakri, A.M.M.A, Mohd, H.K.R.C, Shamsul, B, Rozaimah, R, and Khairatun, N.N, 2006. Concrete Ceramic waste slab. Journal of engineering research and education, Volume 3 139-145. [2] Mahyar, A.A, Reza, N.M, and Milad, T. 2016. The effect of using polyethylene terephthalate particles on physical and strength-related properties of concrete; a laboratory evaluation. Construction and Building Materials 109 (2016) 55-62. [3] Hanifi, B. 2006. Effect of crushed ceramic and basaltic pumice as fine aggregates on concrete mortar properties. Construction and building materials. [4] Gomes, M. Brito, J.D, and Bravo, M, 2014. Mechanical Performance of Structural Concrete with the Incorporation of Coarse Recycled Concrete and Ceramic Aggregates. Journal of Materials in Civil Engineering Volume 26 Issue 10. [5] Bendapudi, S.K, Saha, P, 2011. Contribution of Fly Ash to the Properties of Mortar and Concrete . International Journal on Earth Science & Engineering, ISSN 0974-5904, Volume 04, No 06 SPL, pp.1017-1023. [6] Singh, S, Nande, N, Bansal, P, and Nagar, R, 2017. Experimental Investigation of Sustainable Concrete‖ Made with Granite Industry By-Product. Journal of Materials in Civil Engineering Volume 29 Issue 6. [7] Tangchirapat, W, Rattanashotinunt, C, Buranasing, R, and Jaturapitakkul, R. 2013. Influence of Fly Ash on Slump Loss and Strength of Concrete Fully Incorporating Recycled Concrete Aggregates, Journal of Materials in Civil Engineering Volume 25 Issue 2 - February 2013. [8] Jin, X, and Li, Z, 2003. Effects of Mineral Admixture on Properties of Young Concrete , Journal of materials in Civil Engineering. pp.435- 442 Sept-Oct- 2003. [9] Chandra, S., and Choudhary, R., 2013. Performance Characteristics of Bituminous Concrete‖ with Industrial Wastes as Filler, Journal of Materials in Civil Engineering, Volume 25 Issue 11 - November 2013

[63] Application of GIS into Pavement Management System

Rohan Prakash1 and S.K. Suman2 M.Tech. 1M.Tech. Student, Department of Civil Engineering, National Institute of Technology Patna, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, India E-mail: [email protected], [email protected]

ABSTRACT The principal objective of this study is to reveal the role of GIS technology in the enhancement of PMS. In this paper, the urban road network of Patna city, India having approximate road length of 120 km is studied. A windshield survey was carried over the roads at a very low speed of approximate 10–20 kmph. Two types of Pavements, Flexible and Rigid were studied separately. The road inventory data was also collected at different road segments spaced at 1000m from each other. The PCI value for different road segment was calculated. The PCI values, road inventory data, photos of the location and GPS test location were used as an attribute data for the constructed, segmented lane lines in ArcGIS. 10.3. GIS-based maps are produced to prioritize the road network through color coding for better understanding and visualization of pavement condition for maintenance. Keywords: Pavement Management System, GIS, Windshield Survey, ArcGIS 10.3

1. INTRODUCTION A pavement management system (PMS) is a tool for better decision making regarding pavement management. It examine pavement deterioration due to traffic and weather, and recommend maintenance and repairs to the pavement based on the type and age of the pavement and various measures of existing pavement quality. Measurements can be made by persons on the ground, visually from a moving vehicle, or using automated sensors mounted to a vehicle. PMS often helps the user to create composite pavement quality rankings based on pavement quality measures on roads or road sections. Recommendations are usually biased towards predictive maintenance, rather than allowing a road to deteriorate until it needs more extensive reconstruction. Since the decision of the maintenance is solely depends upon the decision making authority, so it becomes very necessary for a pavement engineer to define his work in a very understanding and effective way. The geographic information system with their spatial analysis capabilities can match the geography of the road network, and GIS is considered to be the most appropriate tools to enhance pavement management operations. GIS display the data in the form of a map, GIS allows the user to interpret, question, track and visualize data. Different pattern and relationships can be made in the form of maps, report and charts. The Integration of GIS into Pavement Management System is the key for better assessment and visualization of pavement condition for maintenance and rehabilitation strategy. It also provides the information regarding the pavement inventory, condition and alternate options regarding maintenance. With the help of GIS, the decision maker can visualize and understand the pavement in a better way through the dynamic color-coding technique for the prioritization of pavement based on their corresponding PCI value. Many researchers have studied about the pavement management system and the role of GIS in PMS. Researcher studied the roads in Kerbala city using PAVER 6.5.7 and also use GIS as a platform for maintenance strategy [1]. In the study of Nahrain university the road which were affected by different

[64] Application of GIS into Pavement Management System distress like weathering, aging, traffic load, and also bad maintenance were taken into consideration [2]. Some researcher studied the Abu Dhabi Island for illustrate the GIS application in pavement management system [3]. According to a research Spatial technologies may enhance the analysis of several transportation- related issues and may improve the quality of decision-making [4]. One researcher showed the advantages of such GIS integration include flexible database editing and ability to display the result and analysis the map through dynamic color-coding [5]. Researcher studied the roads in central and eastern Sudan and came to the conclusion that majority of studied roads need of an emergency program for pavement maintenance, rehabilitation and reconstruction [6]. This paper is based on the work showing the importance of GIS application into Pavement Management System over the urban roads of city Patna, India. The present work consist of the analysis of pavement distresses of Patna city. The objectives of this study are (i) to determine the Pavement Condition Index (PCI) value for Patna road network and (ii) to make prioritization of roads based on the calculated PCI value using ArcGIS for better assessment and decision making.

2. PAVEMENT CONDITION INDEX The present Pavement condition index is based on ASTM (American Society for testing and materials) code Designation: D 6433-07. The PCI of roads was developed by the U. S. Army Corps of engineers [7]. The PCI is an indicator that examines the surface condition of the pavement. PCI ranges from 0 to 100 with 0 being the worst possible condition and 100 being the best possible condition. The calculated PCI value provides a measure of the pavement based on the surface distresses in present condition. It provides a rational and objective basis for determining maintenance needs. Based on the PCI value a verbal description of pavement is maintained that varies from “Failed” to “Excellent” as shown in Table 1.

Table 1: Verbal Description of PCI Values PCI Range Standard PCI Rating Scale Suggested Color 85–100 Good Dark Green 70–85 Satisfactory Light Green 55–70 Fair Yellow 40–55 Poor Light Red 25–40 Very Poor Medium Red 10–25 Serious Dark Red 0–10 Failed Dark grey

3. PAVEMENT CONDITION EVALUATION PROCESS The windshield survey was conducted over the roads of Patna for the collection of distress values. The survey was completed with the help of a car driving at a very low speed of approximately 10-20 kmph. The road was divided into segments of approximately 1km each based on the pavement type and other identifiable starts ends feature. Only one lane, the lane in the worst condition, was rated within each survey segment. The extent of the distresses was estimated by visual inspection. Many times it was not practical for the rater to estimate the exact severity of different distresses, the rating was based on estimating the predominant severity for each distress type. The survey study was done individually for Flexible and Rigid pavement. A survey data sheet (Figure 1&2) was designed showing the road inventory data and the distress data. The distresses accounted for the flexible pavement were longitudinal cracking, transverse cracking, patching, pothole, raveling, edge cracking, block cracking, alligator cracking and shoulder drop-off. The distresses accounted for flexible pavement were linear cracking, shrinkage, patching, divided slab,

[65] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) punch-out, joint seal, faulting, corner break, spalling corners, pop-out, buckling and scaling. The distress severity level were classified into three classes as low, medium and high based on the severity criteria.

Fig. 1: Survey Data Sheet for Flexible Pavement Fig. 2: Survey Data Sheet for Rigid Pavement

4. METHODOLOGY AND FIELD DATA COLLECTION

4.1 Study Area Patna is the capital and largest city of the state of Bihar in India. Patna City is located on the south bank of the river Ganga and it is an important administrative and educational center. The study was done over the urban road network of Patna city having an approximate road length of 120 km. The roads were divided into the different stretches of approximate 1km road length.

4.2 Data Collection The data were collected. a. Primary Data: The road inventory data, pavement distress data. b. Secondary Data: Study area map, Name and Length of different roads.

4.3 Determination of Pavement Condition Index (PCI) Value After the distresses data collection, the next step was to determine the PCI value. The guidelines of ASTM (American Society for testing and materials) code Designation: D 6433-07 was followed for the PCI value calculation. The Table 2 shows the calculation of PCI for a sample section in the study area. The standard PCI uses a scale of 7 different categories based on the calculated PCI value with different colors assigned to different categories as shown in Table 1.

Table 2: The PCI Value Estimation for Sample Section Chainage Distress Units Density Severity Deduct (TDV) m q Value CDV PCI Rating (m) (%) Value Value Patching m2 0.628 L 2 Patching m2 0.514 M 8 Patching m2 0.2 H 8.5

Pot holes Nos 0.057 L 12 Very 0–1000 45.5 8.806 5 20 80 Pot holes Nos 0.028 M 15 Good Block m2 0.114 L 0 cracking Block m2 0.143 M 0 cracking

[66] Application of GIS into Pavement Management System

4.4 Application of ArcGIS in Pavement Management System After the calculation of PCI value, now it is necessary to make a map showing all the essential data for the better understanding and visualization of the concerned roads. The ArcView is a full-featured Geographic Information System (GIS) software for visualizing, managing, creating, and analyzing geographic data. Figure 3 shows the map of Patna city, which was chosen from the Google earth. The file format used for mapping in ArcGIS is “.shp” type. The road map can be loaded to ArcGIS through Google Maps. The following steps were accomplished to integrate PMS data into ArcGIS.

4.4.1 Loading of the Study Area Map into ArcGIS 10.3 A GIS file format is a standard of encoding geographical information into a computer file. The study area map is loaded in the vector data format. The shapefile format is a popular geospatial vector data format for geographic information system (GIS) software. The following steps were followed to import the Google map into ArcGIS. ●● Import the GPS coordinates of surveyed segments over the Google Maps. ●● Create map using the feature of Google Maps as shown in Figure 4

Fig. 3: Patna Map (Study Area)

.s Fig. 4: Google Map Showing Surveyed Spatial Data Location

[67] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Download the created map from Google maps in KML file formate. First you must save your Google Maps Layers created as a .kml file to your hard drive. Make a new folder for the layers you want to export. Now you will import your .kml file using ArcToolbox under Conversion Tools>From KML>KML to Layer in ArcMap as shown in Figure 5.

Fig. 5: Conversion from KML to SHP File Format

4.4.2 Import the Geo-spatial Data in ArcGIS 10.3 Firstly Convert degrees/minutes/seconds to decimal degrees then Enter the Geo-Spatial data of surveyed road section at staring and at end points in excel sheet format. Ensure data frame is set to WGS 1984. Now add excel table to ArcMap. Click on display XY Data and save as feature class.

4.4.3 Import the Road Inventory Data and PCI Value To import the PCI data in ArcGIS corresponding to the surveyed location, merge the PCI value to the corresponding GPS locations in excel sheet format. Click on the Add Data button . Then click the Look in arrow and navigate to the Excel workbook file (.xls), now double-click the Excel workbook file. Then Click the table you want to add to ArcMap, and click Add, as shown in Figure 6.

Fig. 6: The Spatial Data and PCI Value Corresponding to Selected Point [68] Application of GIS into Pavement Management System 4.4.4 Import Raster Dataset as Attributes To import the raster data, click the geodatabase in ArcCatalog or the Catalog window. Click Import > Raster Datasets. Now click on the Input Rasters button to import the raster datasets and Add. Now start an edit session in ArcMap and insert the raster dataset by editing. Figure 10 shows the raster data in ArcMap.

4.4.5 Prioritization of the Roads and Adding Base Map GIS-based maps can be produced to prioritize the road network through color coding for better understanding and visualization of pavement condition for maintenance. To prioritize the roads Right-click the layer in the table of the content then press Properties. Now go to Symbology tab on the layer properties. First click Quantities and now click Graduated colors. Select the PCI data Field value for prioritizing and now Optionally select a Normalization field value. Classify the color ramp into different classes. Double-click on the color symbol to edit the class properties and color . Edit the class range filed based on the standard PCI range for different classes. Figure 12 shows the prioritization of road network. To add Base Map in Arc map, Click the Add Data arrow then click to Add Basemap. Select the required basemap and then click Add.

Fig. 7: Patna Road Network through Color Coding Fig. 8: Raster Data in ArcMap

5. RESULT AND DISCUSSION PCI calculation was evaluated by using the windshield survey method. The results of the PCI value and the road condition for the different road sections are summarized in Table 2. The presumptive measures can be applied on the roads based on the PCI value and a cost effective strategy can be made through Prioritization of the roads. Most of the road are in Satisfactory condition .The result of field survey and PCI value calculation for different road sections are represented in ArcGIS map Figure 9. The information about pavement section can be obtained by clicking over the section on the road map. The roads are prioritized using color coding as shown in Figure 7.

[69] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 9: The Inspection Data of GolGhar Road Section

Table 2: The Details of Different Road Section of Patna City Name of the Road Road Condition PCI Gola road, Banki pur danapur road Satisfactory 81 Digha bridge link road Good 86 Ashiyana-Digha road Ashiyana-Digha road Good 86 ashok rajpath gandhi maidan - gandhi chowk Satisfactory 85 Gandhi chowk to gaya ghat Satisfactory 80 bailey road Satisfactory 74 Golghar road Poor 51.6 Danapur bankipur road Fair 56 budh marg Fair 70 Name of the Road Road Condition PCI mall road Poor 54 church road rigid Fair 70 road no 23 Fair 56.5 danapur doad Poor 51.6 PWD road rigid Fair 70 khazanchi road Fair 57 Langar toli road Fair 70 bakarganj road Fair 56 east boaring canal road Satisfactory 82 birchand patel path Satisfactory 82 station road Satisfactory 78 rajendra path Fair 67 bari path Satisfactory 78 shersah suri road Satisfactory 82 nahar marg Satisfactory 78 arya kumar road Satisfactory 74.2

Table 2 (Contd.)...

[70] Application of GIS into Pavement Management System

...Table 2 (Contd.) Name of the Road Road Condition PCI saidpur road Satisfactory 78.2 bazar samiti road Satisfactory 82 karbigahiya road Poor 54.01 kankarbagh main road Fair 56.44 meethapur station road Fair 64.43 harding road Poor 48.8 khagual road Poor 43.8 Taylor road Satisfactory 77.01 saheed pir ali khan marg Fair 68.68 90 feet road Good 86 kanti factory road Poor 48 boothnath road Satisfactory 71

6. CONCLUSION In this work, the following conclusions can be drawn: 1. The lowest PCI comes out to be “43.8” for Khagol Road, where as the highest PCI comes out to be 86 for “Digha bridge link road, Ashiyana-Digha road and 90-ft road”. 2. Using ArcGIS the assessment of roads can be achieved by visualizing the road data from Map. 3. Priority of maintenance can be manage with the help of color coding technique in GIS application integrated with PCI value. 4. It can be stated from the study that GIS based system provides information for use as a platform on which the issues related to pavement maintenance can be targeted easily and effectively. 5. The limitation with the use of GIS as a tool for PMS is that the data must be updated periodically.

REFERENCES [1] Raid R.A. Almuhanna, Hussein Ali Ewadh, Saja J.M. Alasadi, “Using PAVER 6.5.7 and GIS program for pavement maintenance management for selected roads in Kerbala city.” [2] Asma Thamir Ibraheem, Dua’a Abd AL-Razzaq Falih, “Applying Geographic Information System (GIS) for Maintenance Strategy Selection.” Department of Civil Engineering, Nahrain University, Baghdad, Iraq. [3] Hussein Mohammed Ahmed Elhadi, 2009 “GIS, A Tool for Pavement Management” Department of Urban Planning and Environment School of Architecture (KTH) Stockholm, Sweden. [4] D. Gary, “Pavement Management Applications Using Geographic Information Systems,” Transportation Re- search Board, 2004. http://www.national-academies.org/trb/bookstore. [5] J. Neelam and P.K. Nanda, “Geographical Information System for Pavement Management Systems,” Map Asia Conference, India, 2003. [6] Galal Ali, Mohamed Eisa, Elsir Suleiman, Use of micro PAVER 6.5.7 program for pavement maintenance management system (PMMS) of roads in central and eastern Sudan, J. BRR 12 (July) (2012) (MSc Thesis, Sudan University of Science and Technology). [7] Micro PAVER 6.5.7 6.5.7 User Manual, U.S. Army Corps of Engineering-USACE, USA, 2014.

[71] Investigation and Analysis of Scour Downstream of a Partial Submerged Vertical Weir

Vishal Singh Rawat1, Roshni Thendiyath2, Sudhanshu Raj3, Sandeep Kumar4 and Gaddam Vinay Kumar5 1Ph.D. Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 3,4,5B.Tech (3rd Year Students), Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Scour depth prediction is a key aspect in the design of hydraulic structures. However much detailed literatures exist for the scour design of many hydraulic structures like bridge foundations and dykes, limited study has been carried out for other structures. The present experimental investigation was carried out to study scour dimensions and topography downstream of partial submerged vertical weir. The proposed weir shape was tested to study the probable reduction in scouring at different discharges. MATLAB software was used to examine the spatial variation of scour at the downstream of the tested weir. Keywords: Experimental, Partially Submerged Weir, Scouring

1. INTRODUCTION A Weir is a barrier across the width of the river, usually used to resolve the extreme scouring of the bed, support bed protection, maintain the water level at the upstream side of the structure, and decrease the velocity of flow in the channel. Several equations and expressions to determine or predict the downstream scour have been suggested by researchers [2, 3, 4, 7 and 9]. The removal of sediment such as sand and silt from the bed of a channel by the flow of water is known as hydrodynamic scour phenomenon. Riverine civil engineering structures and channels such as dams, submerged bridges and slice gates are exposed to scour. Deeper scour depths results in the instability of the foundations, may ultimately leads to the failure of the structure. Prediction of the downstream scour of a hydraulic structure plays an important part in their design and has been a matter of broad investigations by many researchers. In the present study the scour depth at the downstream of the partial submerged vertical weir was estimated experimentally. The depth of the scour hole developed was then compared with the scour depth equations given by previous researchers. It was found that the results from the previous studies had good agreement with the observed values of scour. The present study also aims to experimentally check the scouring patterns downstream of the partial submerged vertical weirs along with water surface profiles formed. The experiments were performed for different discharges over the same weir.

2. EXPERIMENTAL SETUP AND PROCEDURES Experiments were performed in a hydraulic flume at the hydraulic and water resources laboratory of National Institute of Technology Patna. The flume used was a recirculating flume with a plunge pool on the downstream side to receive experimented water. Entry of water to the flume is smoothened and a laminar non-aerated flow is ensured at the flume inlet. The flume used had geometric dimensions of 0.30m wide,

7.0m long and 0.50m high. The depth of water at the upstream of the weir (y1) and downstream of the weir (y2) were measured. Discharge was regulated with the help of a flow meter with a least count of

[72] Investigation and Analysis of Scour Downstream of a Partial Submerged Vertical Weir

2.78x10-3 l/s. The approaching Froude number ranged from 0.18 to 0.28 was tested. A uniform bed material was tested for the present experiment. The granulometric characteristics of the bed material is shown in Table 1. Point gauges of 0.01mm accuracy were used for the measurements of exact water depths at various cross sections in the flume. A wooden weir with 10-mm crest width was tested under uniform flow conditions. The weir was fixed to cover the full width of the experimental flume such that 50 mm of the weir was left projected vertically above the flat bed. To ensure a completely submerged flow over the weir, this height of 50 mm above the bed was preferred, it also confirmed a larger downstream scour hole for better measurements. The partially submerged weir was fixed at a distance of 3 m from the inlet of the flume, which ensured fully developed boundary layer. Fig. 1.depicts the schematic layout of the experimental setup.

Fig. 1: Schematic of Experimental Setup

Table 1: Granulometric Characteristics of Bed Materials

Material D60 (mm) D50 (mm) D10 (mm) Uniformity Coefficient (cu) Crushed gravel 6.63 6.12 4.37 1.52

For each experimental run, the test weir was fixed carefully into the flume. The bed was then leveled with the help of a point gauge. To ensure a smoothed and a laminar non-aerated flow at the inlet of the flume, a mesh filter was located. The scour depth and length of scour were measured using the point gauge.

3. DISCUSSION OF EXPERIMENTAL RESULTS

3.1 Water Profiles Measured water surface profiles over the weir for increasing discharges (5-11L/s) are shown in Fig. 2. Water surface profiles may be divided into different regions, (1) Pre-jump region, (2) Post-jump region and (3) tail region.

[73] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

(a) Q= 5 L/s (b) Q= 7 L/s

Fig. 2: Water Profiles Downstream of the Tested Weir for Flow Rates (9-11 L/s)

3.2 Scour Topography Downstream of the Weir (a) Q= 5 L/s (b) Q= 7 L/s

Fig. 3: Scour Topography Downstream of the Weir [74] Investigation and Analysis of Scour Downstream of a Partial Submerged Vertical Weir It was found that scour depth at the downstream depends on the drop height of the vertically placed weir, the increasing flow rate and the size of the bed material. Fig. 3. shows the scour topography downstream of the weir consisting of the scour and deposition topography for all the four flow rates (5-11 L/s). The scour topography is due to the effect of local souring from the free fall of water over the vertical weir, whereas the deposition topography is affected by sediment transport due to the local scour. The deposition topography tends to develop substantially if the scour continues. Also, the scour is limited due to the sidewall effects and the dimensions of the channel.

3.3 Comparison with Previous Literature

Table 2: Equations for Scour Depth Estimation Downstream of the Hydraulic Structures Author Year of Publication Equation for Scour Depth Schoklitsh[8] 1932

Novak[5] 1961

Kotulus 1967

Wu[10] 1973

Melville[4] 2014

Al-Husseini [1] 2019

Fig. 4: Comparison of Observed Scour Depths with Previous Literature

[75] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Many equations for the estimation of scour depth downstream of the hydraulic structures are available [2, 3, 4, 7, and 9]. In the present study few of these equations were used to calculate the maximum scour depths downstream hydraulic structures and calibrated with the, observed values of scour depth in case of the proposed partially submerged vertical weir. Table 2. Shows the scour equations from other literatures used for evaluation, where ys is the estimated scour depth, H is the elevation difference between the upstream water level and tail water level, unit discharge is denoted by q,

D50 is the size of sediment of which 50% of material is finer, D90 is the sediment size of which 90% of material is finer, cs is coefficient with a value of 4.75,V2 is the downstream velocity, Vc is Critical Velocity given by , , , is normalized bed shear stress, , ,

, , ( , , ,

are also parameters) λ η ψ Fig. 4. shows a comparison between the measured scour depths with the equations given by Schoklitsh, Kotulas,δ Melville, Novak, Wu, and Al-Husseini. It was seen that, the scour equations given by Schoklitsh, Kotulas, Wu, Melville and Al-Husseini provide very close values of the scour depth from the measured experimental values. Conversely, equation by Novak gave higher values of scour depth than those computed by other equations and observed ones, this may due to the deviation of sediment size of bed material. However it can be seen that the equation by Wu gave a better assessment of the measured scour depth. Hence it is assumed that, the experimental data from the present work case is satisfactory compared to the equations reviewed from literatures.

4. CONCLUSIONS The present paper is an experimental study of scour development at the downstream of a partially submerged vertical weir. A set of small-scale lab experiments were performed to collect the scour data for uniform bed materials in different flow rates. The maximum scour depth downstream from partially submerged weir was found to be in accordance with the previous studies on scour depth at the downstream of hydraulic structures. The dependency of scour depth on flow rate, for local scour conditions can be used to study the phenomenon of scouring at the foundation of various hydraulic structures. Advanced data is needed to establish the influence of other dependent parameters on scour depth at weirs.

REFERENCES [1] Al-Husseini, Thulfikar Razzak, Abdul-Sahib T. Al-Madhhachi, and Zainab A. Naser. : Laboratory experiments and numerical model of local scour around submerged sharp crested weirs.” Journal of King Saud University-Engineering Sciences (2019). https://doi.org/10.1016/j.jksues.2019.01.001 [2] Bormann, N. E.,Julien, P.Y.: Scour downstream of grade control structures. J.Hydraul. Eng. 117 (5): 579–594 (1991). https://doi.org/10.1061/(ASCE)0733-9429(1991)117:5(579) [3] Guan, D., Melville, B. W., Friedrich, H.: Local scour at submerged weirs in sand-bed channels, J. Hydraul. Res. 54 (2): 172–184(2016) https://doi.org/10.1080/00221686.2015.1132275. [4] Melville, B.W.: Scour at various hydraulic structures: Sluice gates, submerged bridges and low weirs. Australasian Journal of Water Resources. 18(2):101-179 (2014). doi: 10.14264/uql.2014.10 [5] Novak, P.J. :Influence of bed load passage on scour and turbulence downstream of stilling basin. In: 9th Congress, IAHR, Dubrovnik, Croatia (1961). [6] Pagliara, S., Kurdistani S. M. :Scour downstream of cross-vane Structures, J. Hydro-Environ. Res. 7 (4): 236–242. (2013) https://doi.org/10.1016/j.jher.2013.02.002. [7] Schoklitsch, A. Kolkbildung unter überfallstrahlen. Die-Wasserwirtschaft. p. 341 (1932) [in Germany] [8] Wang, L., Melville, B. W., Guan, D..: Effects of upstream weir slope on local scour at submerged weirs, J. Hydraul. Eng.144 (3): 04018002(2018), https://doi.org/10.1061/(ASCE)HY.1943-7900.0001431 [9] Wu, C.M.: Scour at downstream end of dams in Taiwan. IN: Sediment Transportation, Volume 1(1973)

[76] Multi-Criteria Evaluation in GIS for Reconnaissance Survey of Route Selection in Difficult Terrain using Open Source Data and Software

Bhupendra Singh1 and Sumedh Mhaske2 1Post Graduate Student, M.Tech Construction Management, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Associate Professor and HOD, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected], [email protected]

ABSTRACT Route selection is a very tough task especially if it is to be carried out in mountainous regions. Use of GIS in railway route can be very effective as it can consider various engineering as well as non-engineering constraints all at once. In this research two open source GIS software’s are used to develop a methodology for Reconnaissance survey of railway tracks. Firstly, required factors are decided and then Interview was taken of railway authorities to compare them. Importance number are assigned to the factors and sub factors. The factors calculated is used to create dataset and model which can be used to find optimum route. The effectiveness of the model is verified through an already existing route in the region and then is used in a very complex case study of route between Dahanu road and Nashik road. The results shows that this method can find various routes according to multiple inputs which can be easily modified any number of times till optimum result is obtained. Results are discussed along with various merits, shortcomings and possible future developments in the procedure. An extension of the model is discussed for route evaluation from alternative predefined routes and network analysis. Keywords: QGIS, GRASS GIS, GIS, Reconnaissance Survey, Multicriteria Evaluation

1. INTRODUCTION Surveying for route selection in mountainous regions can be a very tedious task because of the undulations and many other engineering constraints along with other non-engineering constraints minimum of 80% of the private and public decision-making is depended on some spatial or geographic aspects[1]. Also this step requires sharp accuracy as the coming steps are fully dependent on the initial survey. Selecting the shortest and direct path for any project may be the goal but many times these goals may contradict because of other objectives[2]. GIS have proved itself to be efficient in the above tasks because of its capacity to deal with both the spatial and non-spatial datasets. To create these datasets Raster maps need to be created in which each raster will have a numeric value depicting the relative cost of route passing through that point. These values were obtained after comparison of the various maps by interviewing Railway authorities and a set of factors obtained which is further divided into sub factors within each map. Method of Importance factor was used for the above comparison. Open source GIS software’s like GRASS GIS and QGIS are growing very fast, moreover very high Quality open source Datasets are also available freely from various sources which are used to create ready Spatial maps (using the above factors and sub factors) which can directly be used to find the optimum route between stations. These inputs and the final resulting maps can be modified any number of times with ease just by changing the factors according to the demands of user.

[77] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Reconnaissance survey in Route selection by Indian railways is done by using inefficient and expensive classical techniques which consists of analysis of analogue maps and ground surveying methods. There is a lot of demand for more than 40 years for a railway track between Dahanu road and Nashik by the people and TDRPA[3-5]. Also the railways have surveyed in the region and came out with a route that was later rejected as it was passing through steep slopes and was incurring extra cost[5]. This area is taken for studying as it has been already proved difficult for surveying by the conventional method .the terrain of the area which varies from 11ft. from MSL at Dahanu road to 2400 ft. from MSL at Nashik. Previous studies of GIS involving shortest paths are studied where GIS has been used to find route of pipelines[2,6,7]. For pipelines main regions where cost reduced were geological elements, elevation differences and soil structure. Other innovative applications of least cost path are evacuating of risky construction sites[8] where similar to cost map risk map was created for least cost path, haul road layout planning[9] and many more. All of them encouraging the use of GIS to improve efficiency. The non- engineering constraints in railway route is studied[2,10] which recommends environmental expert’s views before defining parameters.

2. METHODOLOGY It is divided into three main categories as physical model, GIS model and verification of results. These are shown briefly as follows: 1. Physical Model a. Selection of stations b. Determination of constraints c. Evaluation of constraints by Interview 2. GIS Model a. Data collection b. Building Database and Defining Procedure c. Creation of Raster Cost feasibility map d. Multi-Criteria Evaluation 3. Verification of Results a. Verification of results for NH848 b. Finding optimum railway route From Dahanu road to Nashik

2.1 Physical Model It is defining every raster value in each of the maps according to its relative importance with all the other raster cells in that map and other maps. Relative importance of the maps are found out by comparing them with other maps. Method of importance factor is used for the study. Considered maps are as follows 1. Gradients Flatter Than 4.5 in 100: An ideal railway route should not pass through slopes more than 4.5 in 100[1]. It plays a very important role in deciding the cost 2. Proximity to Rivers and Respective Minimum Elevations Map: these regions are most probable to go under water in excess of rainfall. This map is very important as some places in between have a very high rainfall. Rivers often go through Meandering which can incur extra cost.

[78] Multi-Criteria Evaluation in GIS for Reconnaissance Survey of Route Selection in DifficultTerrain using Open Source Data and Software 3. Respective Maximum Elevations Map: These locations may incur extra cost of tunnels. Railway should have minimum crossings with them 4. Geohazardous Areas: Railway route should avoid areas with high ground acceleration movement. 5. Roads Location: Crossing with a road will incur extra cost and may create an accident prone area. 6. Other Constraints ●● Water bodies ●● Populated areas ●● Swampy grounds ●● Socially or politically conflicted areas Dy. Chief Engineer of central railways, Mr. Shrirang D. Kamble was interviewed to decide the weightage of factors to be considered for the whole map. Following is the table of comparison of the selected maps:

Table 1: Interview Format for Factors Decision Criteria’s Gradients Min and Geohazardous Roads Water Populated No-Go Flatter Than Max Area Location Bodies Areas Areas 4.5 in 100 Relative Levels Gradients flatter than 4.5 in 100 Min and max relative elevations Geohazardous area Roads location Water bodies Populated areas No-Go areas Each dataset (row) is compared against the other data sets (in columns), getting assigned points from 0 to 2. Where, 0,1, an 2 denotes less important, equally important and more important respectively. At the end of each row points are calculated to get the relative sum. Which can be compared with each of the other map to get the relative importance of that map[2]

Table 2: Calculated Importance Factor of Maps Map Name Importance Factor Gradients flatter than 4.5 in 100 1 Minimum and maximum levels 7 Geohazardous area 3 Roads location 6 Water bodies 11 Populated areas 8 NO-GO areas 13 After removing the slope steeper than 10 percent. Calculate the mean slope from Zonal statistics tool plugin in QGIS (in this case it is 4.806). To keep all the maps initially on the same ground keep all raster values initially between 0 to 10 before multiplying it with the Importance factor. [79] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) The maps which have similar features (Population, Waterbody and No-go areas), multiply the mean value with Importance factor. For maps which have more than one feature, can be divided into buffer data in the way shown in following table. The Geohazardous maps have raster values ranging from 0 to 9, so each value is multiplied with 1.111. Table 3 represents all the subfactors, factors, map division and final raster value calculation of each raster block.

Table 3: Raster Cell Calculation of Each Map Mean of raster slope map = 4.806 (values ranging from 0 to 10) Name of Map Sub-division Maps Sub Factors Importance Factor Raster Weightage or Buffers (Whole Map) Gradients - - 1 Each cell is already having slope value Minimum elevation and 0 to 20m 10 7 70 river location 20 to 30m 8 56 30to 40m 6 42 40 to 50m 4 28 50 to 60m 3 21 60 to 70m 2 14 70 to 80m 1 7 Maximum levels 0 to 20m 4.806 7 33.642 Geohazardous area 0-no data 0 3 0 1-low 1.10 3.33 2-low 2.20 6.66 3-low 3.30 9.9 4-moderate 4.40 13.2 5-moderate 5.55 16.65 6-moderate 6.67 20.01 7-high 7.78 23.34 8-high 8.89 26.67 9-high 10 30 Roads location 0 to 20m 10 6 60 20 to 35m 8 48 35 to 40m 6 36 40 to 45m 4 24 45 to 50m 3 18 50 to 55m 2 12 55 to 60m 1 6 Water bodies Selected Areas 4.806 11 52.866 Populated areas Selected Areas 4.806 8 38.448 NO-GO areas Selected Areas 4.806 13 62.478

2.2 GIS Model 2.2.1 Maps Dataset Slope Map: 12.5m DEM is downloaded from Alaska satellite facility. Images from Dataset Sentinel 1B and Sentinel 1A are used. The tiles are provided by NASA, a total 6 tiles were used to cover the data. This data is warped according to EPSG: WGS 84 Zone 43N after that Depressionless DEM is created to [80] Multi-Criteria Evaluation in GIS for Reconnaissance Survey of Route Selection in DifficultTerrain using Open Source Data and Software remove unwanted errors and depressions using algorithm of wang and lu from QGIS plugin. Use r.in.gdal to import the map into grass and then use r.slope.aspect to convert the Mosaic map into slope map as follows: Syntax of r.in.gda[11]l: r.in.gdal [input=DEM_Mosaic] [output=DEM_Mosaic] [band=integer] [memory=integer] [target=name] [title=”phrase”] [location=name]; Syntax of r.slope.aspect[11]: r.slope.aspect elevation=name [slope=name] [aspect=name] [format=string] [precision=string] [pcurvature=name] [tcurvature=name] [dx=name] [dy=name] [dxx=name] [dyy=name] [dxy=name] [zscale=float] [min_slope=float]; Actual command: r.slope.aspect.exe elevation=slope@PERMANENT slope=Slope_Raster format=percent –a; Slopes steeper than 10 percent were removed using if(x,a,b) from r.mapcalc in GRASS console using following commands, where output Slope_Raster_Mean is used to calculate mean and Slope_Raster_ edited is used for Raster calculations r.mapcalc Slope_Raster_Mean= if( Slope_Raster>=10, null(), Slope_Raster); r.mapcalc Slope_Raster_edited= if( Slope_Raster>=10, 63.4, Slope_Raster); Relative Minimum Elevations and Maximum Elevation Map: From the same DEM Mosaic after removing depressions Strahler Algorithm is run to find the minimum and maximum relative algorithms. Create Strahler orders from 1 to 10 and then remove first seven strahler’s to calculate minimum elevations and possible rivers location. Use channel network and drainage basins in QGIS to show basin locations which is the relative highest elevations. Create buffers as defined in Physical Model and put the following weightage in buffer maps of road so as the raster addition will give required cumulative weightage. Convert them to Raster and then add them to GRASS dataset using r.in.gdal.qgis. Add all the above maps to create a single Raster layer using r.mapcalc. This final map will have the required weightage as defined in physical model. The required buffer values of river and maximum elevation map can be calculated in the similar fashion.

Table 4: Provision of Buffer Map Values (Road map) Buffer Distance Weightage Required Sub_Factor in Buffer Map 0 to 60m 6 6 0 to 55m 12 6 0 to 50m 18 6 0 to 45m 24 6 0 to 40m 30 6 0 to 35m 48 12 0 to 20m 60 12 Populated Areas, Waterbodies Map, Road Map, No-Go Areas: Digitize them in a new Shapefile of Linestring Data or polygon Data Use Google Earth to know the actual locations. Geohazardous Areas: Data is retrieved from NASA SEDAC Earthquake hazard distribution – Peak ground acceleration. A direct Plugin of “QuickMapServices” will provide above data.

[81] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 1: River Locations and Minimum Elevation Map

Fig. 2: Peak Ground Acceleration Map

Fig. 3: Roads Location Map

[82] Multi-Criteria Evaluation in GIS for Reconnaissance Survey of Route Selection in DifficultTerrain using Open Source Data and Software

Fig. 4: Rural and Urban Populated Areas Map

Fig. 5: Maximum Elevations Map

Fig. 6: Slope Map (Percentage)

[83] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 7: Water Bodies Map

2.2.2 Map Raster Calculations a. Connect all the worked raster maps in Grass GIS as “r.mapcalc final_raster = (((((((Slope_Raster_edited + min_level_buffer)+ max_level_buffer)+ water_ body)+Road_buffer)+Populated_areas)+Geohazardous_areas));” b. Use r.cost in GRASS GIS to create final cost feasibility Raster Map which can be created with following syntax[13]: r.cost [-knrib] input=name output=name [solver=name] [nearest=name] [outdir=name] [start_ points=name] [stop_points=name] [start_raster=name] [start_coordinates=east,north[,east,north,...]] [stop_coordinates=east,north[,east,north,...]] [max_cost=value] [null_cost=value] [memory=value] -k flag i.e Knight’s move can be used for more accurate results. Co-ordinates of starting points are put as East and North. This cost feasibility Raster Map will have each raster value showing the cumulative cost of reaching that point from the co-ordinates provided by the user c. Use r.drain and put the co-ordinates of final point to find the least cost path. r.drain traces a flow through a cost surface on a raster map. Its syntax is as follows[13]: r.drain [-cand] input=name [direction=name] output=name [drain=name] [start_ coordinates=east,north[,east,north,...]] [start_points=name[,name,...]]

Fig. 8: Final Cost Feasibility Raster Layer Created

[84] Multi-Criteria Evaluation in GIS for Reconnaissance Survey of Route Selection in DifficultTerrain using Open Source Data and Software 2.2.3 Verification of Model Verification of Dataset and Model for NH848: Region of NH848 that is the road connecting Nashik from Trimbak to Jawahar is considered for verification because This road passes through the areas with steep change in slopes moreover, It has constraints in its course like Water bodies. Populated areas and Streams and lowest elevations. It produced the following Results. Total length of the already existing road = 51.260 kms Total length of route formed by GIS = 46.279 kms Total length of non-overlapping route = 11.86 kms Fig. 9 proves the validation of model as most of the calculated route from model is overlapping with the already existing road. About 12 km of route in between is not overlapping with the existing road because of high cost as shown in fig. 10 and the reason for this high cost is shown in fig. 10 that is high slope in the region. Thus, fig. 10 and fig. 11 in combination verifies the validity of cost map feasibility raster map. Moreover because the route is passing through a flatter slope, its curvature is also lesser in the non-overlapping region as shown in fig. 9

Fig. 9: NH848 Verified Route Over Already Existing Road

Fig. 10: NH848 Verified Route Over Cost Map

[85] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 11: NH848 Verified Slope Layer Finding optimum railway route From Dahanu road to Nashik Running this model between these two station’s coordinates gave the following results:

Fig. 12: GIS Created Railway Route Overlapped Over all the Constraints

Table 5: Features of GIS Created Railway Route between Dahanu Road and Nashik Total Length of Route 142.269 kms Number of perpendicular river crossings 3 Number of perpendicular crossings against maximum elevation 4 Number of perpendicular crossings against roads 5 Length of route passing through populated areas 1.331 kms Length of route passing through water body 0 kms Length of route passing through region with ground acceleration movement factor more than ‘5’ 0 kms Length of route passing through region with ground acceleration movement factor equal to ‘4’ 15.314 kms

3. SUMMARY & CONCLUSION 1. A route which is best suited against all the decided constraints and which requires minimum cut and fill (as it passes through minimum slope) can be obtained using open source software’s and data using the defined methodology.

[86] Multi-Criteria Evaluation in GIS for Reconnaissance Survey of Route Selection in DifficultTerrain using Open Source Data and Software 2. Also, for the selected road i.e. NH 848 the obtained road from GIS calculations is most of the time overlapping with the already existing surveyed road. This proves the validity of the procedure. The results shows that obtained result for roads is better than the actual road as it is both shorter and will require lesser cut and fill which can be easily seen from the overlap of drain layer over the cost map. 3. A suitable set of factors which can be used to find the route is achieved from the Interview. The final factors obtained from the Multi-criteria evaluation can be always doubtful, but once all the dataset is created in GIS, datasets can be easily modified according to the demands of user any number of times with ease. 4. If the area is far too high in slopes then, route can be selected from some predefined routes. The same method can also be used for analysis of best route out of more than one route. Following extension in the above model is recommended for this a. Find the accumulated points of minimum cost. b. Join them using straight lines. c. Create buffers for the lines, thus obtain a polygon data. d. Clip the cost data according from using mask layer as defined above. e. Now marking the initial and final points use r.drain to find the minimum cost path in the preselected routes.

Fig. 13: Proposed Method of Finding Least Cost Rote of Railways in Predefined Paths

REFERENCES [1] Kiema J, Karanja F (2007). “GIS-Based Railway Route Selection for the Proposed Kenya-Sudan Railway: Case study of Kitale-Kapenguria Section”, Journal of Cold Regions Engineering, vol. 04 . PP. 79-90 [2] Volkan Y, Recep N, Yomralioglu, Tahsin, Uzun (2009). “Raster-based GIS data guide economic pipeline construction” Oil & Gas Journal; Apr 7, 2008; 106, 13; ABI/INFORM, pp. 62-68 [3] TDRPA urges for ‘Dahanu-Nashik’ rail link (18 june 2018), The united news Agency,http://www.uniindia.com/tdrpa-urges- for-dahanu-nashik-rail-link/states/news/1263902.html -19 sept 2018 [4] Survey on Dahanu-Nashik rail link project underway: RTI (28 may 2016), The Economic Times, http://www.uniindia.com/ tdrpa-urges-for-dahanu-nashik-rail-link/states/news/1263902.html -19 sept 2018 [5] Survey again for Dahanu-Nashik Railway (19 september 2018), The Loksatta Team, https://www.loksatta.com/thane-news/ survey-again-for-dahanu-nashik-railway-1754560/ -21 sept 2018 [6] Kang M. W, Jha M K., Buddharaju R. (2014). “Raster-based GIS data guide economic pipeline construction”, Journal of Transportation Engineering, Vol. 140, No. 1,doi: 10.1061/(ASCE)TE.1943-5436.0000445 [7] Kennelly P, Gamarra A (2015), “gis suitability modeling to support a pipeline route selection”, Presented at the ESRI User Conference in San Diego, CA. July, 2015 [8] Meouche, M, Abunemeh, I, Hijaze A. Mebarki, I. (2017).” Developing Optimal Paths for Evacuating Risky Construction Sites”’ Journal of Construction Engineering and Management,144(2): 04017099, doi: 10.1061/(ASCE)CO.1943- 7862.0001413 [9] Kang S, Seo J. (2013). “GIS Method for Haul Road Layout Planning in Large Earthmoving Projects: Framework and Analysis”, Journal of Construction Engineering and Management, Vol. 139, No. 2, doi: 10.1061/(ASCE)CO.1943- 7862.0000561. [10] Ali A. D , ahad S B, Majid M (2008) “Environmental consideration in railway route selection with GIS(Case study: Rasht- Anzali railway in Iran)” , Journal of Environmental Studies vol. 33(44), pp65-72 [11] Grass GIS 7.6 manual https://grass.osgeo.org/grass76/manuals/index.html

[87] Superpave Mix Design for DBM in Indian Scenario

Digvijay Singh Chauhan1 and Sumedh Mhaske2 1 M.Tech. Student, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Associate Professor and HOD, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected], [email protected]

ABSTRACT Construction of roads is important for the growth of a nation. However, due to various reasons, the flexible pavements undergoes frequent repairs and deteriorates before design life of the pavement. Performance depends on Pavement & Mix Design. Bituminous Concrete (BC) layer as well as Dense Bituminous Macadam (DBM) layer in flexible pavement is the layer that is prone to vehicular loads, and thus its design and quality is the top priority while designing. This study emphasizes on use of Superpave Method for design of DBM. Specimens were prepared for DBM designed using Marshall Method as well as Superpave Method for enabling easier comparison. Certain criteria’s were common in both the methods and hence adopted for comparison of the methods w.r.t. Performance. Superpave mix has shown better performance & suggested for field trial. Keywords: Dense Bituminous Macadam, Marshall Mix Design, Superpave Mix Design, Flexible Pavement

1. INTRODUCTION

1.1 General Throughout the 21st century, road infrastructure in the country has been the primary focus for the development. Major projects have been initiated under National Highway Development Program (NHDP) by the Government of India. India. India has the second largest road network as on 31st March, 2016, at 1.7 km of roads per sq. km. of land, which consists of highways, paved & unpaved roads, which are constantly being improved [4]. Indian road network has grown from 399,942 km in 1950–51 to 5,603,293 km in 2015-16 [4]. Roads in India are generally bitumen based macadamized roads. Two things are of major considerations that affects the cost & performance of the road – pavement design and the mix design. The pavement design is based on the factors like soil bearing capacity, CBR value of the sub-base, road traffic volume and life of pavement. The mix design is based on the gradation of aggregates, bitumen binder content & fillers for the required strength of the layer.

1.2 Need of the Study The bitumen is the mostly used and costly resource in the bituminous road construction. Indian roads have poor performance with pavement life much shorter than the expected life. Distress like potholes, bleeding shoving, rutting, undulations and rutting appears early on bituminous surface due to various reasons like high traffic intensity in terms of commercial vehicles, overloading of trucks and variation in daily & seasonal temperature of the pavement. The top layers of the bituminous road consists of approximately 5.0 to 6.0 % of bitumen. In India, Marshall Mix design is used for determining the bitumen content, aggregate gradation, filler, thickness of the layers & laying temperatures. In developed countries like USA, Superpave Mix design is used which provides better performance in lesser bitumen content when compared with Marshall Mix design for Asphalt Concrete. [88] Superpave Mix Design for DBM in Indian Scenario

1.3 Objectives of Study In this project, the mix design of dense bituminous macadam was prepared using Marshall as well as Superpave guidelines by considering the location as Mumbai and the tests for rheological properties, viscosity, and the performance were performed. The selected parameters for comparison were Optimum Binder Content, Marshall Stability & flow value, and Asphalt film thickness. Objectives of the study: ●● To compare the Marshall Mix design & Superpave Mix design for Dense Bituminous Macadam for Indian conditions. ●● To perform tests to measure the performance of Dense Bituminous Macadam prepared using Marshall & Superpave guidelines.

2. BACKGROUND Roberts et al. (2002) studied the history of mix design concepts from the 1900’s to 2000s, and mentioned that the bituminous paving techniques used were Pat test, Habbard field method, Hveem Test and Marshall Test [10].

2.1 Marshall Mix Design As per Indian standards and recommendations like MORTH & IRC, Marshall Test is used for design of bituminous mixes. In a bituminous mix, aggregate gradation and mix design requirements is of primary concern. Various mixes have various gradation. There are different requirements for different mixes w.r.t to volumetric parameters & Marshall Stability and mix design is required to find OBC.

2.2 Superpave Mix Design Superpave (SUperior PERforming asphalt PAVEments) was prepared by Strategic Highway Research Program (SHRP), includes standard specifications, test methods, and engineering practices enabling appropriate material selection, mix design of HMA to meet the climatic & traffic conditions of specific roadway paving projects [3]. There are three basic steps in mixture design: 1. Selection of Materials: Based on: a) Environment, b) Traffic, and c) Pavement structure. 2. Selection of a Design Aggregate Structure (Design Blend): Determining the aggregate proportions and corresponding combined gradations of the mix design. 3. Selection of Design (Optimum) Asphalt Binder Content: Varying the amount of asphalt binder in the design aggregate structure to obtain acceptable volumetric properties when compared to the established mixture criteria. Bansode and Mhaske (2015) studied the use of Brookfield Viscometer for evaluation of temperature at plant mixing, field placement and compaction for Superpave design mixes to ensure pumpability during delivery and plant operations and stated that the ideal Mixing temperature ranges from 152°C to 158°C and Compaction temperature ranges from 140°C to 145°C for the Superpave mixes [3]. Wang et al. (2000) stated that the Superpave mixtures were less susceptible to permanent deformation [8]. Swami et al. (2004) suggested that though stability and flow value is not the design criteria in Superpave, but to compare with Marshall Method, accordingly the tests were performed and found that the Superpave mix had 27% higher stability and fulfill all the criteria for easy and good construction at less binder content than mixes prepared Marshall Mix [2]. Lee et al. (2018) studied the performance grades of asphalt binder as per Superpave specifications to design the pavements in North Korea as seasonal temperature changes causes’ distress of rutting & cracking in asphalt pavements. First step was to establish high & low [89] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) temperatures for a location and temperature zoning for developing PG map. The research concluded that PGs with 50% reliability can be used for low volume roads and PGs with 98% reliability for high volume roads considering the economy of the country [9]. Al-Khateeb et al (2013) conducted a laboratory study for rutting performance of Superpave Asphalt mixes of basalt and limestone aggregates at various temperatures (40, 50, 60 and 65) and axial load of 2.5kN with loading frequency of 8Hz using dynamic creep test and observed that basalt aggregates performs much better in terms of rutting performance [6].

3. EXPERIMENTAL SETUP & RESULTS The materials were sourced from Mumbai region. Bitumen of penetration grade 60/70 grade is used for preparing the test specimens as it is the most commonly used grade of bitumen for pavement works. Aggregates in Maharashtra are basaltic in nature, and as per the past studies basalt aggregates performs better in terms of rutting performance, thus basalt aggregates of sizes 20mm and 10mm is used. Stone dust shall be used if fine aggregates is deficient in material passing in 75 µm sieve.

3.1 Bitumen Testing Basic Tests on bitumen were conducted & the results obtained were shown in Table 1 [7].

Table 1: Characteristics of Bitumen Sr. No. Test Test Method Results Spec. Limit 1 Specific Gravity IS 1202 1.03 0.99 min. 2 Penetration IS 1203 66 60-70 3 Ductility IS 1208 108 40 min. 4 Softening Point IS 1205 47 47 min. 5 Viscosity using rotational viscometer at 135°C ASTM D 4402 0.34 Pa.s Max 3 Pa.s 6 Rolling Thin Film Oven (% Mass loss) AASHTO T 240 0.77% Max 1% Mass loss

3.2 Aggregates Testing Basic tests on aggregates was performed to ensure the quality for use in pavement as per IRC 94-1986. Tests conducted and the results were shown in Table 2.

Table 2: Characteristics of Aggregates Sr. No. Test Test Method Results Spec. Limit 1 Aggregate Impact Value IS 2386 Part IV 11.65% Max 35 % 2 Los Angeles Abrasion Value IS 2386 Part IV 17.22% Max 40 % 3 Aggregate Crushing Value IS 2386 Part IV 21.83% Max 40 % 4 Flakiness Index IS 2386 Part I 11.47% Max 35 % 5 Water Absorption IS 2386 Part III 0.3% Max 2 %

3.3 Job Mix Formula for DBM by Marshall Method Sieve Analysis and proportioning of materials i.e. 10mm and 20mm aggregates, stone dust was in conformance to MORT&H as per the thickness required. For the study, compacted thickness of DBM layer was considered as 75mm and accordingly the grading was adopted for gradation criteria as shown in Table 3 [7].

[90] Superpave Mix Design for DBM in Indian Scenario

Table 3: Gradation of Mineral Aggregate in the Mix as Per MORT&H [7] Sieve Size Grading as Per MORT&H Trial Blend Grading (mm) (% Passing) (% Passing) 37.5 mm 100 100 26.5 mm 90–100 100 19.0 mm 71–95 74.375 13.2 mm 56–80 56.5 4.75 mm 38–54 38.75 2.36 mm 28–42 28.25 300 µm 7–21 7.25 75 µm 2–8 2.125 Marshall Mixes were prepared with blended mineral aggregates by incrementing bitumen content by +0.5% within range of 4.5% to 6%. For each binder content, 3 specimens were prepared and tested for bulk density, stability, and flow value. The following graphs were plotted after averaging the values obtained: Binder content vs. corrected Marshall Stability, vs. Marshall Flow, vs. percentage of void (Vv) in the total mix, vs. voids filled with bitumen (VFB), and vs. unit weight or bulk specific gravity (Gm). The Optimum Binder Content will then be determined by taking average value of the following three bitumen contents found from the graphs obtained [9]: Binder content (B.C.) corresponding to max stability, corresponding to max Bulk specific gravity (Gm), and corresponding to the median of designed limits of percent air voids (4% Vv) in the total mix.

3.4 Job Mix Formula for DBM by Superpave Method The first step is to select asphalt binder and aggregates based on the environment and traffic loading at the project location and accordingly the bitumen binder grade is selected and design air temperature is obtained. Since, the bitumen of penetration grade of 60/70 is used for Marshall Method, thus for comparison purpose the same bitumen is used for preparing of tests specimens. Second step is to select the design aggregate structure, for which 3 trial-blends were prepared and compared to the specification requirements. Gradation control points based on max sieve size, nominal max sieve, 12.5mm sieve, 2.36 mm sieve and 0.075 mm sieve. Restricted zone is an area on either side of the max density line starting at the 4.75 mm sieve and extending to 0.3 mm sieve. Table 4 indicates the gradation criteria for 25.0 mm Nominal Maximum size aggregate [4].

Table 4: Gradation Criteria of 25.0 mm Nominal Maximum Size Aggregate as Per SHRP-A-407 [4] Minimum Maximum Trial 1 Trial 2 Trial 1 Sieve Size (% Passing) (% Passing) (Intermediate) (Coarse) (Fine) 37.5 mm 100 – 100.00 100.00 100.00 25.0 mm 900 100 97.00 91.00 99.00 19.0 mm – 90 89.50 89.50 89.50 2.36 mm 19 45 38.00 25.00 44.00 0.075 mm 1 7 4.00 2.00 1.50 Restricted Zone 4.75 mm 39.5 39.5 40.00 40.00 45.00 2.36 mm 26.8 30.8 38.00 25.00 44.00 1.18 mm 18.1 24.1 25.00 17.90 27.00 0.6 mm 13.6 17.6 19.00 12.50 18.00 0.3 mm 11.4 11.4 11.40 12.00 11.40

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Table 5: Mix Criteria for Estimated Trial Asphalt Binder Content as Per SHRP-A-407 [4] Properties Trial 1 (Intermediate) Trial 2 (Coarse) Trial 1 (Fine) Criteria Values

Bulk Sp. Gravity (Gsb) 2.667 2.652 2.501 Initial Trial Asphalt binder content 5.31% 5.19% 5.028% Volumetric Criteria % Air Voids 4.0 % 4.0 % 4.0 % 4.0 % % VMA (25.0mm NMAS) 15.74 % 17.14 % 15.75 % Min. 12.0% % VFA (< 0.3 million ESALs) 69.82 % 63.05 % 69.63 % 67 – 80 % Dust Proportion 0.76 0.38 0.29 0.6-1.2 Estimated Trial Asphalt Binder Content 5.176% SAY 5.25% After establishing the mix volumetric properties, reviewing the data and Intermediate blend is within the acceptable criteria, thus selected as design aggregate structure. The next step was to select Design asphalt binder content. Once the structure was selected, specimens were compacted at several asphalt binder contents and the mixture properties were then evaluated w.r.t. asphalt binder content. Three specimens were prepared & compacted at each of the following asphalt contents: estimated asphalt binder content, estimated asphalt binder content ± 0.5%, and estimated asphalt binder content ± 1.0 %, i.e., 4.25%, 4,75%, 5.25%, 5.75%, 6.25% were prepared. From these data points, plots of % air voids, % VMA, % VFA and density versus asphalt binder content were prepared as shown in figure 1. Design binder content at 4% air voids was established and evaluation of mix properties to verify the volumetric criteria as per the Table 5 above [4].

3.5 Results & Comparison of Marshall Method with Superpave Method for Design of DBM The plotted graphs for both the mixes was prepared as shown in figure 1 below.

Corrected Marshall Stability Marshall Flow

Percentage of Voids VFB (%) [92] Superpave Mix Design for DBM in Indian Scenario

BC Marshall Superpave @ Max St 4.50 % 5.75 % @ Max Gm 5.50 % 6.25 % @ 4% Vv 5.286 % 5.768 % Avg. (OBC) 5.095% 5.92% %VFB at OBC 66.028% 79.880% Flow at OBC 3.79 2.98 Stability at OBC 720.72 kg 1150.37 kg %VFB Reqd. 55-75% 67-80% Min. 340 kg 2-4 Stability & Flow (Stability) (Flow) Bulk Specific Gravity Summary Fig. 1: Comparison of Results The difference in flow value obtained for DBM mix designed using Superpave was 0.8, which indicates better performance of the mix and pavement will be showing distresses at a later period. The following Comparison criteria were selected considering the parameters common to both the methods:

3.5.1 Optimum Binder Content The Optimum Binder Content as per the design mix prepared as per the guidelines by considering Mumbai location and locally available materials, i.e. Bitumen of penetration grade 60/70 and basalt aggregates, for the mix comes at 5.095% and 5.92% by Marshall & Superpave method respectively. Stability and Flow Stability and Flow is not a criterion in Superpave method, but for comparison purpose this criteria was used. As per the plotted graphs, there is significance improvement in the strength and flow of the DBM Mix when designed using Superpave guidelines, i.e., stability obtained was 1.18 times from that obtained when designed using Marshall guidelines indicating better moisture damage resistance of the mix. Asphalt Film Thickness Asphalt Film Thickness was calculated using surface area method and surface area factor was taken as per Table 8.1 of MS-2 (7th edition, Asphalt Institute). The gradation of the aggregates in the mix is used to calculate the surface area of the total aggregate. [1].

Table 6: Surface Area Factors as Per MS-2 (7th Edition, Asphalt Institute) [1] Total % Passing Maximum Size 4.75 2.36 1.18 600 µm 300 µm 150 µm 75 µm Sieve No. (36.5 mm to 9.5 mm)* mm mm mm S.A. m2/kg 0.41 0.41 0.82 1.64 2.87 6.14 12.29 32.77 *Because of the relatively small surface area of larger aggregate sizes, a single surface-area factor of 0.41 m2/kg is used to account for the surface area of all of the material retained on the 9.5 mm sieve, regardless of the maximum aggregate size. The results for DBM Mix designed using Marshall guidelines was 288.8625 m2/kg and by Superpave guidelines was 481.926 m2/kg. It indicates that the thick Asphalts films ages and hardens slowly and effectively seals greater % of interconnected air voids in pavement which reduces air & water penetration.

4. SUMMARY & CONCLUSION Though the design process as per Superpave guidelines consumes more time in lab testing, it has shown improved quality and performance of the mix. To determine the type of binder required as per PG grading, the method of weather data analysis is suggested in parts of India where minimum temperatures [93] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) go below 0°C. The design aggregate structure concept of five control points and restricted zone has shown improvised properties of the mix and proved effective in mixing with the binder. It enabled to form a mix having higher Asphalt film thickness value. The ideal Mixing temperature ranges from 152°C to 158°C and Compaction temperature ranges from 140°C to 145°C for the Superpave mixes. Since, DBM is a wearing course and is not directly susceptible to moving loads; hence, its performance as per Superpave guidelines should reduce routine & cyclic maintenance costs incurred on the pavement for design life. Superpave design procedure has been a successful method in countries like US for over a decade, and has shown remarkable performance of the roads as well as significant cost savings. In the future scope, one must conduct field studies on a pilot patch to study the long-term performance of the pavement under actual loading.

REFERENCES [1] Asphalt Institute (2014), “Asphalt Mix Design Methods”, MS-2, 7th edition, Asphalt Institute, USA. [2] B.L. Swami, Y.A. Mehta & S. Bose (2004). “A Comparison of the Marshall and Superpave Design Procedure for Materials Sourced in India”, International Journal of Pavement Engineering, 5:3, 163-173, DOI: 10.1080/10298430412331309115, Taylor and Francis. [3] Bansode, R., and Dr. Mhaske, S., (2015), “Flexible Pavement: Superpave Mix Design”, International Journal of Modern Trends in Engineering and Research (IJMTER), Volume 2, Issue 7, [July-2015] Special Issue of ICRTET’2015, e-ISSN No.:2349-9745, Pg. 902-906. [4] “Basic Road Statistics of India 2015-16”, Ministry of Road Transport & Highways, India (Retrieved on 28 August 2018) [5] Cominsky, R., (1994), “The Superpave Mix Design Manual for New Construction Overlays”, SHRP – A – 407: 1994, Strategic Highway Research Program, National Research Council, Washington, DC (172). [6] Ghazi G. Al-Khateeb, Taisir S. Khedaywi, Turki I. Al-Suleiman Obaidat, and Ahmad Mirwais Najib (2013), “Laboratory Study for Comparing Rutting Performance of Limestone and Basalt Superpave Asphalt Mixtures”. Journal of Materials in Civil Engineering, Vol. 25, No. 1, January 1, 2013. © ASCE, ISSN 0899-1561/2013/1-21-29. [7] IRC 94 (1986), “Specification for Dense Bituminous Macadam”, Indian Roads Congress, India. [8] J.N. Wang, T. W. Kennedy and R. B. McGennis, (2000), “Volumetric and Mechanical Performance Properties of Superpave Mixtures”, Journal of Materials in Civil Engineering Vol. 12, No. 3, August, 2000. ASCE, ISSN 0899-1561/00/0003-0238– 0244., ASCE. [9] J.-S. Lee, J.-H. Kim, O.-S. Kwon and B.-D. Lee, (2018), “Asphalt binder performance grading of North Korea for Superpave asphalt mix-design”, Int. J. Pavement Res. Technol. (2018), https://doi.org/10.1016/j.ijprt.2018.06.004, Elsevier. [10] Roberts, F. L., Mohammad, L. N. and Wang, L. B. (2002). “History of hot mix asphalt mixture design in the United States”, Journal of Materials in Civil Engineering, ASCE, pp. 279-293, ASCE.

[94] Development of Sustainable Building Blocks using Fly Ash Blended with Different Additives: A Critical Review

Bibhakar Kumar Singh1 and Siddhartha Sengupta2 1Research Scholar, Department of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, India 2Associate Professor, Department of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, India E-mail: [email protected], [email protected]

ABSTRACT Fly ash may be mixed with other substances to efficiently produce bricks/tiles and other building blocks. Approximately 180 million ton of fly ash is generated annually in India. Only a small part of it gets utilized. The disposal of rest amount poses great environmental risks. Utilization of fly ash in making building materials is economically beneficial as well as provides a solution to the dumping problem (of fly ash). In the present paper a critical review has been done on investigations carried out on making of bricks and other building blocks using fly ash mixed with different additives. About 18 research articles spanning over a period of last 25 years are reviewed in this write-up. Building blocks (made of fly ash with other materials/ aggregates) of diverse kinds such as unfired/ fired bricks, impact resisting tiles, precast paver blocks, dry pressed ceramic tiles have been taken into account. It is observed that different binding materials like lime, sodium silicate, sodium hydroxide, gypsum, portland cement, phosphogypsum are commonly used in manufacturing of above building units. Some of the different substances blended with fly ash are clay, natural sand and gravel, pulverized fuel ash, high calcium wood ash, industrial waste slag, red clay brick waste, quarry dust etc. Some of the important findings of the research works done by different scientists indicated that the wet compressive strength of clay-fly ash bricks was 40 % better than the good quality clay bricks; the water absorption of fly ash – lime- gypsum bricks was found to be in the range of 18 to 36 %; the water absorption and porosity showed a decreasing trend on addition of bottom ash. Keywords: Fly Ash, Building Blocks, Compressive Strength, Water Absorption, Porosity

1. INTRODUCTION Building blocks such as unfired/ fired bricks, impact resisting tiles, precast paver blocks play an important role in building and construction field for thousands of years. The first building block/ brick produced by human beings traced back to 10,000 BCE, found in Egypt [1]. The ancient city of Ur (modern Iraq) was the first site where clay bricks were used as building materials. Dating back to 5000 BCE, there has been some records about using fire to produce clay bricks to yield better mechanical properties and performance. Since then many research works have been done using new advance machinery to find out the ways to improve the quality of bricks/ building blocks. Presently the demand of such materials is sky touching, and availability of raw materials is limited, it is necessary to find some other alternative materials to produce high performance building blocks. In this review article about 20 papers are taken into account spanning over a period of last 25 years to study the research works in the area of utilization of fly ash/ other additives in building industry.The current annual production of coal fly ash worldwide is estimated around 600 million tonnes,the amount of coal waste (fly ash), produced by thermal power plants has been increasing throughout the world, and the disposal of the large amount of fly ash has become a serious environmental problem. India is the sixth largest electricity generating and consuming country in the world. The Ministry of Power, Govt. of India estimates 1800 million tons of coal use every year and 600 million tons of fly

[95] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) ash generated by 2031-2032. Fly ash when blended with different types of additives can produce high quality building blocks. In past many research work were carried out to know the behaviour of fly ash when blended with different additives, and its usefulness to make different types of building blocks. Fly ash and clay mixture can produce good quality of bricks. Results indicated that the incorporation of fly ash significantly affected the compressive strength of bricks Moreover, the density (of bricks) decreased up to 18% with the increase of fly ash content and resulted in lightweight bricks. There are many advantages of Light weight bricks, they have excellent compressive strength as compared to regular clay bricks, they save a huge amount of resources in foundation and structure, and hence more economical building can be made by using light weight bricks [2]. Fly ash, when mixed with lime and gypsum results in superior quality bricks. Investigations of Reddy and Gourav [3] revealed that the lime-fly ash ratio in the range of 0.3–0.5 with 2% gypsum resulted in good quality FaL- G (Fly ash – lime – gypsum) bricks. Sokolar and Vodova [4] evaluated the utilization of fluidized fly ash for the manufacturing of dry pressed ceramic tiles; fly ash-clay mixture was mixed with limestone, blast furnace slag to produce the above tiles. Impact resistance tiles can be also developed by blended fly-ash cenospheres/clay composites at high temperature [5]. Murugesan et al. [6] examined the performance of precast paver blocks made of fly ash and different additives. These blocks were found to have a strength of about 30 MPa which was quite above the minimum specified limit.

2. FLY ASH CHARACTERIZATION

2.1 Chemical and Mineralogical Compositions As it may be observed, fly ash posses a complex chemical composition. The very different chemical composition they have is related to various factors such as coal composition, pulverization degree, design of the furnace, combustion process conditions, and nature of ash collection. The fly ashes are essentially composed of silica (SiO2), alumina (Al2O3), and iron oxide (Fe2O3) with lesser amounts of Ca, Mg, Na, K, P, Ti, and Mn oxides. The Indian low-lime fly ashes are characterized by relatively higher concentration of

SiO2 and Al2O3 and lower contents of Fe2O3. This makes the fly ashes potentially valuable sources of oxides for the manufacture of fired clay masonry building blocks. Fly ash, when mixed with lime and water, forms a compound similar to Portland cement, this makes fly ash suitable as a prime material in blended cement, mosaic tiles, and hollow blocks, among other building materials. The higher concentration of SiO2, Al2O3, and Fe2O3 makes fly ash even more suitable for this purpose. Table 1. represents a typical composition (in terms of oxides) of Indian fly ash.

Table 1: Typical Composition of Indian Fly Ash Oxides Concentration (%)

SiO2 45.00–65.25

Al2O3 14.00–31.10

Fe2O3 3.00–15.00 CaO 0.10–6.50 MgO 0.20–3.90

Na2O 0.6–1.0

K2O 0.3–1.0 Source: Shakir et al. 2013 [7]

2.2 Physical Characterization The fly ash is a fine powdery waste material with color varying from gray to black, depending on the amount of unburned carbon. The fly ash particles exhibit distinct morphologies of various shapes such as

[96] Development of Sustainable Building Blocks using Fly Ash Blended with Different Additives: A Critical Review spherical and irregular (with a predominance of spherical) particles. The specific gravity of fly ash usually ranges from 2.1 to 3.0 [8], depending on the iron oxide content (hematite and magnetite). The specific surface area of fly ash usually ranges from 0.17 to 12.40 m2/g [9] This particle size range is compatible with the size range of common clays used to produce fired clay masonry bricks. In terms of soil mechanics, the fly ash can be classified as a non-plastic material [10]. Thus, when added to a clay or shale, it influences the plastic behavior, conformation, and drying of the clayey body. This means that a clay or shale of high plasticity should be selected for use in the clay/fly ash mixes.

3. BUILDING BLOCKS PRODUCED BY FLY ASH BLENDED WITH DIFFERENT ADDITIVES There are different types of building blocks produced from the mixture of fly ash and additives e.g. fired/ unfired bricks, fire resistance tiles, paver blocks. Additives like gypsum, lime, phosphogypsum, red clay brick waste powder, stone waste powder are used in different proportions to make various building blocks. The production methodology of above-mentioned building blocks includes mixing, molding, drying firing etc. and use of different bonding agents such as cement, lime and others chemicals.

3.1 Fly Ash-based Fired Clay Masonry Brick Processing Figure 1 depicts the flow chart of the main steps used to produce fired clay masonry bricks incorporated with fly ashes. Researchers have used different fly ashes and common clays (having a very broad range of chemical, mineralogical, and physical characteristics) and also adopted different processing conditions to produce fired clay masonry bricks.

Raw Materials: - Fly ash, cement, gypsum, lime, phosphogypsum, clay

Fly ash mixed with different additives through Mixer (additives mixed according to needs)

Pressing and extrusion

Drying 60–110°C in an oven And after that air dried

Firing Slow-firing cycle T = 800OC -1200OC

Fig. 1: Flowchart for the Industrial Production of Fired Clay Masonry Bricks

[97] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

3.2 Tiles and Paver Blocks Production Technique using Blended Fly Ash Different types of tiles and light weight blocks is produced by blended fly ash mixture at different temperature. In past a few research works showed very promising results in terms of the mechanical properties and durability of the produced building blocks such as roofing tiles, impact resisting tiles, fire resistance tiles; which were manufactured by adding some suitable additives in fly ash at different percentage. The quantity of additive varied according to fly ash properties and its mineralogy. Building blocks such as tiles and paver blocks contain more amount of bonding agent such as, cement, lime, gypsum hence their mechanical properties enhanced with time.

4. SYNTHESIS OF LITERATURE A number of research papers have been reviewed, identifying many key issues regarding the characteristics, manufacturing processes of the building blocks and their potential uses in construction field. Additives added fly ash mixture showed very promising results. In past so many works were carried out to know the best way to utilize fly ash for making different building blocks, although using fly ash for this purpose is not an easy task, because of its non-cohesive nature and its mineralogical limitation. Some of the important literature and their findings related to above issues/ topic are mentioned in Table 2.

Table 2: Major Findings of Some Important Research Work Researchers Raw Materials Firing Process/ Compressive Strength Comments/ Major Findings Used (for Building Blocks/Brick Production) Leiva et al. [11] Clay, Fly Ash 17.2 MPa at 10000 C Fly ash used as raw material for replacing clay to make fired bricks was an effective measure for saving land and decreasing pollution. Zang et al. [12] Slag, fly ash, Glass waste- Firing up to 1040 and 11000C, In all raw materials Fly ash and glass municipal solid max compressive strength= 20-35 MPa industry waste indicated promising waste, plastic results in terms of mechanical as waste glass Plastic waste - Firing in a furnace between durability properties. industry waste 900 and 12000C for 2 hrs at the ramp of 10C/min, max compressive strength= 10-15 MPa

Municipal waste - firing to 9000C at a ramp of 20C/min until 6000C then 50C/min; 2 hr soaking time,

Fly ash - Unfired: mixing; moulded; drying at room temperature for 2 days; oven- drying at 600C for 4hrs and 1000C for 6 hrs. Al-Fakih et al. [13] Municipal solid Fly ash-Sun drying for 4-5 d, fired at 8000C Various studies concluded that waste, tannery in kiln for 3 days. CS ranged from 19 - 8.0 utilizing waste materials to produce waste, rice MPa FS ranged from 5.7 - 3.0 MPa masonry bricks could contribute to husk, waste sustainable construction materials coal, fly ash Municipal waste=Molded + oven dried and eco-friendly building products. (1050C) and then burnt under 850, 9000C firing temp. CS ranged from 27.2 - 9.96 MPa

Tannery waste = 24 hr natural drying, 48 hr of oven drying (1050C) and heated at 900, 950, and 10000C CS: ranged from 10.98 – 29.61 MPa

Table 2 (Contd.)...

[98] Development of Sustainable Building Blocks using Fly Ash Blended with Different Additives: A Critical Review

...Table 2 (Contd.)

Researchers Raw Materials Firing Process/ Compressive Strength Comments/ Major Findings Used (for Building Blocks/Brick Production) Masuka et al. [14] Coal fly ash, Coal fly ash - CS ranged from 19 - 8.0 MPa Overall finding demonstrated that lime, wood FS ranged from 8 - 10 MPa unfired bricks with compressive aggregates. strength higher than of cement added Lime - CS ranged from 19 - 8.0 MPa FS bricks could be developed. ranged from 10 - 25 MPa Castellanos et al. [5] Clay, fly ash, Mixture of clay +fly ash+ filler is used to This study had shown very promising filler make impact resistant tiles. results of adding fly-ash with clay for reducing the density and improving the dynamic impact response for potential application in roofing tiles. Wang et al. [15] Fly ash, The strength of fly ash non-load-bearing It was concluded that the new Cement, bricks could reach over 25 MPa, if cement technology of brick making could Aggregates, added into the mixture the strength of bricks consume a large amount of fly ash Additive could reach up to 40 MPa. and industrial wastes. Fly ash could be used as the main raw material in the production of fly ash bricks, with its proportion reaching as high as 50–80. Fonseca et al. [16] Clay, fly ash, The compressive strength results range In samples fired at 900 °C, significant additives from42 MPa in 900 0C/0% samples to 85 improvements in mechanical strength MPa in the fired bodies at 1100 °C and with were verified. The addition of 20% the addition of 10% of ash. of bottom ash produced a strength increase of more than 20% when compared to reference samples. Sokolar & Vodova Clay, fluidized 9 to 12 MPa after firing at 10000C It was possible to modify the fly [4] fly ash, ash–clay raw material mixture with fluidized fly ash (FFA) so that the firing shrinkage of a body due to sintering was compensated due to creation of anorthite during firing. Some major research works in the field of utilizing fly ash with different additives to prepare bricks and other building blocks such as tiles, paver blocks etc. are discussed below. Freidin and Erell [17] studied the water uptake and water absorption of prepared samples made of fly ash and industrial slag. The principal objective of the research was to develop a technology for the production of blocks or bricks made of coal fly-ash, slag, and water-glass, cured in the open air. The effect of increasing the compaction pressure and the content of water glass on the compressive strength and the water uptake were observed. Ways of reducing water uptake and water absorption were also examined. The test results showed that the water-resistant building materials might be made out of mixtures of coal fly-ash, Lime-slag and water-glass (A solution of sodium silicate in water). Their compressive strength (2.0-20.0 MPa) and water resistance were greatly affected due to the formation of a water stable binder consisting of silica gel and high-module potassium silicate. However, such materials characteristically had a large water uptake up to 40%, which is due to the high absorption capacity of fly-ash. The reduction of water uptake to within acceptable limits for comparable wall materials, such as clay bricks, silicate bricks, and concrete blocks, can be achieved by adding a hydrophobic material such as Siloxane CS to the mixture in very small quantities. However, this reduced the compressive strength of the blocks considerably. Kumar [18] evaluated the mechanical properties of bricks made of fly ash, lime, and phosphogypsum. Fly ash-lime-phosphogypsum (FaL-G) bricks are one of the best alternatives to conventional burnt clay bricks and cause less damage to the environment during its manufacturing process. This paper gave

[99] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) the results of an experimental investigation in which the compressive strength, water absorption, density and durability of Fly ash-lime-phosphogypsum (FaL-G) bricks were investigated by using the varying percentage of fly ash, lime, and calcined phosphogypsum. The properties of Fly ash-lime-phosphogypsum (FaL-G) bricks were compared with those of the ordinary burnt clay bricks. Based on the experimental investigation reported in this paper, it was observed that the strength of FaL-G bricks increased with age, and water absorption of FaL-G bricks was found to be in the range of 18.8 to 36.3 percent, whereas the water absorption for ordinary burnt clay bricks should not be more than 20 percent. It was also observed that water absorption of FaL-G bricks increased with high fly ash content. Dondi et al. [9] examined the chemical stability of clay bricks containing 6% fly ash. The development of efflorescence, the amount of water-soluble salts and their effect on bricks were studied. The fraction of S, V, Ni, Mg, Ca, Na and K immobilized in the ceramic matrix, and the number of volatile elements potentially released during the firing was determined by ICP–OES, XRPD, TGA, SEM and EMP analyses. The quantity of ash added to the matrix affected the chemical stability of clay/ash mixtures; however, it was opined that the industrial brick making technique in which firing was done at moderate temperatures, did not allow the complete inertization of ash. In effect, all magnesium and nickel, together with most vanadium, were immobilized in the crystal structures of silicates constituting the ceramic matrix; on the other hand, a large part of sulphur, as well as a small but significant amount of vanadium, remained in water-soluble form. Furthermore, the firing reactions between clay and ash promoted mobilization of calcium and alkalis; consequently, efflorescence was strongly increased. These phenomena appeared to be unacceptable even for ash additions as high as 1.5%; there was, moreover, a noticeable risk of sulphate attack to the mortars in brick masonry. Ahmaruzzaman [8] reviewed the utilization of fly ash in the construction industry, and as a low-cost adsorbent for the removal of organic compounds, flue gas and metals, lightweight aggregate, mine backfill, road sub-base, and zeolite synthesis. Understanding the combustion processes and dumping process provides both a background and futuristic approach to handling the huge amount of fly ash. According to this review work it was found that fly ash is a promising adsorbent for the removal of various pollutants, using fly ash for adsorption of NOx, SOx, organic compounds, and mercury in air, dyes and other organic compounds in waters is found to be more suitable option as compare to other chemical process. The adsorption capacity of fly ash may be increased after chemical and physical activation. in the future, the alkali activation technique provides us a novel type of building material using a huge amount of fly ash. Sokolar and Vodova [4] investigated the influence of fluidized fly ash in fly ash– clay body after firing at 1080oC. Studies were carried out to find water absorption, bulk density, apparent density, apparent porosity, and bending strength. It was found that the limited shrinkage after firing the fly ash–clay mixture may be achieved by the addition of limestone, which however decreased the bending strength of the body. Addition of Fluidized fly ash (FFA) in the fly ash–clay mixture decreased the firing shrinkage of the test samples. With an increased content of FFA in the raw material mixture the porosity of the fired body increased. Its water absorption and apparent porosity were also increased, but bulk density and bending strength decreased. The results indicated that the maximum amount of FFA was used with high temperature fly ash and kaolinic clay to produce dry pressed ceramic tiles. Diop et al. [19] studied the performance of bricks made of two different types of clay treated at different temperature. Two different clay samples with different alkali concentrations (4, 8 and 12 M NaOH) were used to form thick paste (alkali activation). After vigorous hand-mixing, the treated clays were statically compacted in a 2.5 cm diameter cylinder. The compaction was carried out by a hand-operated hydraulic press. The reaction of the clay with 8 M or 12 M NaOH continued for a long time. It was seen that the alkali activation enhanced the overall stability of the soils. Sukmak et al. [20] evaluated the role of influential factors on the strength development in clay-fly ash geopolymer. Silty clay was used as fine aggregates and fly ash is used as pozzolanic material. The Clay fly [100] Development of Sustainable Building Blocks using Fly Ash Blended with Different Additives: A Critical Review ash geopolymer was a mixture of alkaline solution (Na2SiO3/NaOH), clay and fly ash. The ratio of fly ash to clay was 0.3; the Na2SiO3/NaOH ratios were 0.4,0.7 ,1.0 ,1.5 and 2.3. It was observed that the specimen’s strength was varied for different ratio after curing. On the basis of this research article it is concluded that the optimum Alkali/FA ratio was dependent only upon the fly ash replacement (FA/clay ratio). Shakir et al. [7] investigated the properties of brick made of fly ash, quarry dust, and billet scale. The procedure for making the bricks included mixing the constituents along with cement and water, and then forming the bricks within mold without applying pressure over them. Unlike the traditional method of brick manufacturing, the new approach used less energy. The quarry dust and cement were firstly placed in a mixer and dry mixed for 2 min. Billet scale and fly ash were then added and mixed for another 2 min. The mixer was kept covered with burlap (wet tissue) during mixing to avoid the volatility of materials. Water was then added to the constituent materials and mixed for another 2 min, after that the mixture was then poured in moulds of size (200 X 90 X 60) mm. The moulds were covered with wet tissue overnight and then transferred to the curing environment in plastic storage boxes at a temperature of 22OC. The compressive strength ranged in (7.7–26.3) MPa for brick made with quarry dust and (6.2–16) MPa for brick made of billet scale. Fonseca et al. [16] evaluated the suitability of reusing (in brick making) coal fly ash generated from power plants. They determined the chemical and mineralogical composition of both clay and fly ash. The materials were analyzed by a scanning electron microscope and X-ray diffraction, after that Six different mixtures of clay/bottom ash were prepared: clay without residue and with the following additions of bottom ash: 2.5 wt.%, 5 wt.%, 10 wt.%, 15 wt.% and 20 wt.%. Based on the findings reported in this paper, some conclusions can be made: The plastic behaviour of the clay/bottom ash mixtures was slightly worse when compared to clay mixture, hence it was recommended to use plasticizers to improve the paste plasticity. It was also concluded that in samples fired at 900 °C, significantly improve the mechanical strength. Pawar and Garud [21] studied the effect of varying percentage of fly ash in clayey mixture to produce ecofriendly bricks. The main objective of this research work was to develop bricks with good strength after replacement of clay by fly ash. The results showed that the bricks made of 15% fly ash with 85% clay had sufficient strength to be used as a no-load bearing member of building. The overall results were better compared to lime bricks and clay bricks. The wet compressive strength was 40% better than good quality clay bricks and lime bricks. Yang et al. [22] added fly ash in proportion of 0% to 20% by weight with iron tailings to increase the quality of the produced bricks at 9000C to 10000C firing temperature. The results showed that, regardless of the firing temperature, the porosity and water absorption also increased. A reduction in bulk density (2060-1860 kg/m3) and compressive strength (26-15.8 MPa) were measured with the increase in fly ash content but they were still within the requirements of the building bricks codes. Leiva et al. [23] examined the feasibility of utilizing fly ash for the production of green bricks. The fly ash from coal based thermal power plant was used as raw material to replace clay to make fired bricks. The effect of fly ash with high replacing ratio (from 0 to 80%) of clay on properties of bricks was analyzed. The cylindrical specimens with 32.5 mm diameter and 50 mm length, were manufactured by compressing at 10 MPa. After that the specimens were fired at three different temperature 8000C, 9000C, and 10000C. The compressive strength decreased with ash content for samples treated at 800 and 900°C. This property was closely linked to the density. This trend was inverted for a firing temperature of 1000 °C, where the compressive strength increased by increasing the percentage of fly ash added. According to this research article the major finding was that the compressive strength was affected by increasing temperature, bricks with high ash content at 10000C had highest compressive strength. Naganathan et al. [24] studied the performance of bricks made using fly ash and bottom ash. Bricks were cast using self-compacting mixtures of bottom ash, fly ash, cement with ceratain percentage of lime and

[101] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) gypsum into it. After pressing and firing, bricks were tested for compressive strength, modulus of rapture, ultrasonic pulse velocity (upv), water absorption, initial rate of suction, fire resistance and durability. It was found that the strength of bricks ranged between (7.13–17.36) MPa which was higher than strength required for conventional bricks. Strength increased with increase in fly ash. The peak value of strength was attained for the mixture with bottom ash: fly ash ratio of 1:1.25 and with bottom ash/cement ratio of 0.45. Modulus of rupture of bricks were higher than that of the normal clay and cement bricks. Durability of all the bricks was better compared to normal clay bricks. The water absorption of fly ash – lime- gypsum bricks were found to be in the range of 18 to 36 %; the water absorption and porosity showed a decreasing trend on addition of bottom ash. Baharuddin et al. [6] studied the performance of burnt clay-fly ash bricks and unburnt bricks. In the study, clay bricks and unburnt fly ash bricks were collected from different production units and their characteristics were evaluated. Compressive strength of brick was determined as per IS: 3495 (Parts 1):1992 (Reaffirmed 2002) [25]. Five bricks were taken for testing in each case. Bricks were immersed in water bath at a temperature of 25 °C for 1 day. Afterwards, the specimens were taken out and allowed to dry in room temperature. Cement mortar was prepared with proportion of 1:3 and used to fill the frog of bricks to achieve uniform section. Bricks were kept at room temperature for 24 hours and then immersed in clean water for an additional 72 hours. Significant variations and lack of quality controls for fly ash unburnt bricks was observed in the study compared to specifications in the standard. Variation in fly ash characteristics was a main reason for poor quality of fly ash unburnt bricks. Therefore, proper physical, chemical, and mineralogical characterizations were necessary for sources fly ash to guarantee its reactivity before selection for manufacturing process was suggested. Holmes et al. [26] studied the performance of masonry block incorporated with incinerator bottom ash as a substitution of fine aggregate. Results showed direct effects in the mechanical properties of the developed bricks where compressive strength (10.7-4.0 MPa), flexural strength (2.3-1.0 MPa) and density (2214-2009 kg/m3) decreased with the increase of incinerator bottom ash content. In contrast, the permeability of water was increased with increase in bottom ash content which increased from 7.0% to 20.4%. The study concluded that the optimal proportion of bottom ash should not be more than 20% of the total fine aggregate. Abbas et al. [2] studied the mechanical and durability properties of the fired (at 800° C) clay bricks manufactured using fly ash (FA, 0- 25 wt%). Results indicated that the incorporation of fly ash significantly reduced the compressive strength and bending strength, of the produced brick, by more than 50% compared to the conventional clay bricks. Moreover, the density decreased up to 18% with the increase of fly ash content and resulted in lightweight bricks while the porosity and water absorption (15% - 24%) increased with the increase of fly ash percentage and thus resulted in low compressive strength (about 8 MPa) and low bending strength (3 MPa). Cheah et al. [27] evaluated the strength development mechanism in brick made of pulverized fuel ash and high calcium wood ash. Primary aim of the study was to report mechanical strength performance of the block produced by pulverized fly ash (PFA) and high calcium content wood ash (HCWA) with small contents of geopolymer. It was seen that in HCWA-PFA hybrid geopolymer paste system, as the HCWA content increased, the amount of mixing water required to achieve standard consistency increased proportionally due to the angular particle shape and the porous nature of HCWA in comparison with PFA. Zhang et al. [12] studied the properties of clay based geopolymer bricks. They opined that Geopolymerisation was a preferable way to produce building blocks/bricks, but corresponding cost and benefit analyses needed to be conducted to reveal the opportunities. Clay-based geopolymer bricks could be one of the focuses of future brick-related research, and the key challenge was to produce the clay-based geopolymer in a less energy-intensive way.

[102] Development of Sustainable Building Blocks using Fly Ash Blended with Different Additives: A Critical Review

Table 3: Effect of Firing Temperature on Compressive Strength Raw Materils Used Firing Temperature Maximum Compressive Strength Lime + clay + fly ash 600–8000 C 10–15 MPa Clay + fly ash 600–10000 C 15–25 MPa Cement + fly ash – 6–15 MPa Gypsum + fly ash + stone dust/quarry dust – 10–50 MPa Fly ash + activator – 25–85 MPa (based on curing technique) Fly ash + red clay brick waste (powder) 800–1000 0 C 15–28 MPa

Fly ash: Clay 40:50, Leiva et al. [23] Fly ash:Clay 50:50 , Linling et al. [28] Fly ash:Clay 60:40, Linling et al. [28] Fly ash:Clay 70:30 Akhtar [29] Fly ash:Clay 80:20, Sokolar et al. [4] 100

Compressive Strength (MPa) (MPa) Compressive Strength 0 990 1000 1010 1020 1030 1040 1050 1060 Firing Temperature in Degree C

Fig. 2: Compressive Strength Comparison at Different Firing Temperature for Various Clay: Flay Ash Ratio According to Table 3 it is clear that unfired bricks show less strength as compared to fired bricks. Different additives like stone dust, lime, quarry dust, gypsum also play an important role in terms of strength but proper bonding between particles. When the firing temperature is raised, the compressive strength increases, this is due to the sintering process, which improves the link between particles, and increases its mechanical strength. The results also indicated that the strength diminished with the increasing amount of ash in the brick, due to the lower contents of ashes in sintering agents K2O + MgO, [11]. Especially, for bricks it had been seen from previous researches [2. 16, 23] that the compressive strength depended greatly on firing temperature. The firing temperature and clay: fly ash ratio greatly affect the compressive strength of bricks, as well as different building block. As it has been depicted in Figure 2, it is clear that if the percentage of fly ash is more than that of clay the strength decreases dramatically. The most preferable combination is 50% fly ash mixed with 50% clay which shows maximum compressive strength.

[103] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 5. CONCLUSION An extensive critical review of production methodology of building blocks using fly ash (mixed with other material) has been done in this paper. A number of benchmark research works have been taken into account to know the best suitable additives, processing technique and method of manufacturing. Different parameters such as, compressive strength, water absorption, efflorescence, breaking load, weight per unit area are considered. It is found the use of additives (with fly as) such as cement, lime, gypsum, phosphogypsum etc. produces superior quality building blocks having considerably high compressive strength. Other properties like water absorption, bulk density, efflorescence etc. are also improved. Firing temperature plays an important role to enhance compressive strength, and durability; at high temperature sintering process takes place, resulting bonding between particles. Alkali activation is the chemical process in which sodium silicate and sodium hydroxide mixed solution react with silica and alumina contain material such as coal fly ash to make alumina- silicate crystalline chain. Alkali activated fly ashes is the cement for the future. Alkali activation process transform glassy structures (partially or totally amorphous and/or metastable) into very compact well-cemented composites. Some of the limitations of the reported studies are that; It is also found that the results obtained by the previous researchers have not verified numerically. Different standard softwares like ANSYS, ABAQUS may be used to make simulated models of masonry built with the developed bricks/ tiles etc. and their efficacy may be tested.

REFERENCES [1] Campbell J, Pryce W (2003) Brick: A world history. Thames & Hudson London. [2] Abbas S, Saleem MA, Kazmi SMS, Munir MJ, (2017) Production of sustainable clay bricks using waste fly ash: Mechanical and durability properties, J. Build. Eng., 14: 7-14 [3] Reddy BV, Jagadish K (2003) Embodied energy of common and alternative building materials and technologies, Energy Build. 35(2): 129-137 [4] Sokolar R, Vodova L (2011) The effect of fluidized fly ash on the properties of dry pressed ceramic tiles based on fly ash–clay body. In: Ceramics International 37 (2011) 2879-2885. Elsevier Science Limited, doi: 10.1016/j.ceramint.2011.05.005 [5] Castellanos AG, Mawson H, Burke V, Prabhakar P (2017) Fly ash cenosphere/clay blended composites for impact resistance tiles, construction and building materials, Elsevier, doi.org/10.1016/j.conbuildmat.2017.08.151 [6] Murugesan T, Bahuruddin A, Sakthivel M, Vijay R, Sakthivel S (2016) Performance evaluation of Burnt Clay-Fly Ash Unburnt Bricks and precast paver blocks. In: Materials Today: Proceedings 4 (2017) 9673–9679. Elsevier Science Limited, Selection and Peer-review under responsibility of International Conference on Recent Trends in Engineering and Material Sciences (ICEMS) [7] Shakir AA, Naganathan S, Mustapha KN (2013) Properties of bricks made using fly ash, quarry dust and billet scale. In: Construction and Building Materials, 41:131-138. Elsevier, doi: 10.1016/j.conbuildmat.2012.11.077 [8] Ahmaruzzaman M (2010) A review on the utilization of fly ash. In: Progress in Energy and Combustion Science, 36:327–363 [9] Dondi M, Guarini G, Raimondo M, Ruffini A (2002) Orimulsion fly ash in clay bricks—part 3: chemical stability of ash-bearing products. In: Journal of the European Ceramic Society 22:1749–1758. Elsevier Science Limited [10] De Silva JS, Perera BVA (2018) Effect of waste rice husk ash (RHA) on structural, thermal and acoustic properties of fired clay bricks. J. Build. Eng. 18: 252-259 [11] Leiva C, Galan M, Arenas C, Farinas B, Peceno B (2018) A mechanical, leaching and radiological assessment of fired bricks with a high content of fly ash, Elsevier, Ceramics International, doi.org/10.1016/j.ceramint.2018.04.162 [12] Zhang L (2013) Production of bricks from waste materials: A review, Constr. Build. Mater. 47:(Supplement C): 643-655 [13] Al-Fahih A, Mohammed BS, Liew MS, Nikbakht E (2019) Incorporation of waste materials in the manufacture of masonry bricks: An update review. Journal of Building Engineering, 21: 37-54 [14] Masuka S, Gwenzi W, Rukuni T (2018) Development, engineering properties and potential applications of unfired earth bricks reinforced by coal fly ash, lime and wood aggregates, J. Build. Eng. 18: 312-320 [15] Wang L, Sun H, Sun Z, Ma E (2015) New technology and application of brick making with coal fly ash. Mater Cycles Waste Manag. Springer, DOI 10.1007/s10163-015-0368-9 [16] Fonseca BS, Galhano C, Seixas D (2015) Technical feasibility of reusing coal combustion by-products from a thermoelectric power plant in the manufacture of fired clay bricks. In: Applied Clay Science 104: 189-195 [17] Freidin K, Erell E (1995) Bricks made of coal Fly-ash and slag, Cured in the open air. In: Cement & Concrete Composites 17: 289-300 [18] Kumar S (1999) Fly ash-lime- phosphogypsum cementitious binder: A new trend in bricks. In: Materials and Structures/ Mat6fiaux et Constructions, 33:59-64

[104] Development of Sustainable Building Blocks using Fly Ash Blended with Different Additives: A Critical Review

[19] Diop MB, Grutzeck MW, Molez L (2011) Comparing the performances of bricks made with natural clay and clay activated by calcination and addition of sodium silicate. In: Applied Clay Science, 54:172-178 [20] Sukmak P, Horpibulsuk S, Shen S-L (2013) Strength development bin clay-fly ash geopolymer. Construction and Building Materials 40:566-574 [21] Pawar AS, Garud DB (2104) Engineering properties of clay bricks with use of fly ash. International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308, Volume: 03 Special Issue: 09 | NCETCE-2014 [22] Yang C, Cui C, Qin J, Cui X (2014) Characteristics of the fired bricks with low-silicon iron tailings, Constr. Build. Mater. 70:36-42 [23] Leiva C, Arenas C, Farinas BA, Vilches LF, Peceno B, Rodriguez-galan M (2016) Characteristicsof firedbrickswithco- combustion fly ashes. Journal of Building Engineering, 5:114-118 [24] Naganathan S, Mohamed AYO, Mustapha KN (2015) Performance of bricks made using fly ash and bottom ash. Construction and Building Materials, 96: 576-580 [25] IS:3495 (Parts 1):1992 (Reaffirmed 2002) Methods of tests of burnt clay building bricks. Bureau of Indian Standards, New Delhi [26] Holmes N, O’Malley H, Cribbin P, Mullen H, Keane G (2016) Performance of masonry blocks containing different proportions of incinator bottom ash, Sustainable Mater.Technol, 8: 14-19 [27] Cheah CB, Part WK, Ramli M (2017) The long-term engineering properties of cementless building block work containing large volume of wood ash and coal fly ash. Constr. Build. Mater. 143:522-536 [28] Lingling X, Wei G, Tao W, Nanru,Y (2005). Study on fired bricks with replacing clay by fly ash in high volume ratio. Construction and Building Materials, 19. http:// dx.doi.org/10.1016/j.conbuildmat.2004.05.017. [29] Akhtar MN (2017) Resource efficient brick. [30] http://www.resourceefficientbricks.org/pdf/REB_booklet_Mar2017.pdf [accessed 5th May, 2019]

[105] A Sustainable Approach to Subgrade Stabilization using Coir Fiber: Performance and Cost Evaluation

Shaikh Arshad1 and Dr. Sumedh Mhaske2 1 M.Tech. Student, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Associate Professor and HOD, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected], [email protected]

ABSTRACT Construction of highway pavement governs so many crucial activities, at times we may encounter unstable or weak soil. Being the bottom most layer of pavement, subgrade has to withstand loads of overlying layers along with vehicular load. For highway pavement to be strong enough to withstand designed loads, subgrade should be sufficiently compressed and stable, else weak subgrade will cause damage to pavement by settlement such as cracking, potholes, rutting and eventually would result in early failure of pavement. To deal with unstable or weak subgrade, we need to process it with either mechanical, physical or chemical methods. In this study, we have stabilized the subgrade using short & thin coir fibers. Coir fiber is a sustainable and cheap material which when used in specified orientation and in optimum quantity can cause significant improvement in bearing capacity, strength and other engineering properties of soil. CBR test was conducted on unreinforced and fiber reinforced soil samples to evaluate their strength. The obtained results have shown significant increase in CBR value upto 2.639 times higher than that of unreinforced sample. Furthermore, cost comparison was undertaken for three widely used methods of soil stabilization viz. conventional rubble soling, use of Geogrid and use of coir fibers. It was found that reinforcing coir fiber is the optimum method of soil stabilization in terms of cost. Keywords: Subgrade Strength, Coir Fiber Reinforcement, CBR Test, Sustainable Soil Stabilization

1. INTRODUCTION Highway pavement consist of many layers such as wearing course, base course, subbase course and subgrade. Being the bottom most layer of a road pavement, subgrade should be strong enough to support the overall loads coming over it. If subgrade is not stable then it will cause damage to road pavement by settlement such as rutting, pothole and eventually would result in early failure of pavement. Practically it is impossible to have fully stable subgrade along the whole stretch of road or railway alignment. Usually we encounter weak or soft soil such as clay, silty soil at frequent intervals depending upon the regional properties. There are various methods to deal with such unstable soil such as replacement of soil, use of Geogrid, mechanical compaction, chemical stabilization, fiber reinforcement etc. Replacement of soft or weak soil with stable soil involves large amount of labours, equipments, time and cost, hence not a feasible solution especially when hauling distance is significantly large. Use of Geogrid and conventional compaction methods also imparts sufficient strength to the soil but reinforcing natural fiber can be economical, time saving and eco-friendly, as natural fibers are easily available, cheap and a sustainable material. Moreover fiber reinforcement is effective in all types of soil i.e. silt, sand and clay. California bearing ratio (CBR) is an empirical test used mainly to measure the bearing capacity of soil as a subgrade material in the design of pavement. The California bearing ratio test is penetration test meant for the assessment of subgrade strength of roads and pavements [9]. (1) CBR =

[106] A Sustainable Approach to Subgrade Stabilization using Coir Fiber: Performance and Cost Evaluation 2. LITERATURE REVIEW Among many other factors, service life of pavement is mainly dependent on subgrade. Soft soil forms problematic subgrade due to its low bearing capacity and strength. Subgrade forms receiving platform for pavement layers and hence should be strong enough to withstand weight of overlying pavement layers and also the weight of wheel load coming over it. Soft soil does not possess sufficient strength, so pavement constructed over such soils are subjected to early degradation (Peter et al., 2016). The escalating cost of materials and energy and lack of resources available have motivated highway engineers to explore new alternatives in building new roads and rehabilitating the existing ones. Reinforcing the subgrade soils with short fibers is one such alternative (Chandra et al., 2015). Increase in strength in soil is due to the interaction of fiber with the soil particle through surface friction and interlocking. It transfers the stress from the soil to the fiber by its tensile strength (John et al., 2018). Soil reinforcement is a technique to improve the engineering characteristics of soil in order to develop the parameters such as shear strength, bearing capacity, compressibility, density, and hydraulic conductivity. The primary purpose of reinforcing soil mass is to improve its strength, to increase its bearing capacity and to reduce settlements and lateral deformation (Hejazi et al., 2011). The maximum increase in CBR value of reinforced sample was observed at 0.6% fiber content having a CBR value 4 times that obtained for plain soil (Peter et al., 2016). The CBR of Soils A, B, and C was found to be 1.16, 1.95, and 6.20%, respectively. These values increased to 4.33, 6.42, and 18.03%, respectively, due to reinforcing the soil at optimum fiber content (Chandra et al., 2015). As the jute fiber content is increased, the CBR value of jute reinforced soil sample further increased and this increase is remarkable at fiber content of 0.75% (Hamid et al., 2017). As fiber content increases, CBR value also increases further and are substantial at 1% fiber content. Maximum CBR value of coir reinforced soil is 3.3 times (519%) that of plain soil at a fiber content of 1% (John et al., 2018). The addition of 1% polyester fiber of Aspect Ratios (AR) 200 & 400, increases the CBR by 1.54 and 1.25 times respectively than the unreinforced soil samples (Rao and Jayalekshmi 2010). CBR value of soil increases with the increase in fiber content to some extent, and further addition of fiber results in decreased strength due to excess organic matter content (Kumar et al., 2015). Natural fibers can be used as reinforcement to strengthen the soil in six fields including pavement layers, railway embankment, stability of slope, retaining wall, earthquake and foundation soil. Furthermore, natural fibers are suited in all types of soil (Hejazi et. al.2011). There is significant effects of length of fiber on the CBR value of soil, it increases with the increase in length of fiber (Hamid et al., 2017). The rate of increase in CBR is higher when fibers with higher aspect ratio are added. This is because of higher tensile strength of the fibers (Rao and Jayalekshmi 2010). Larger diameter of fiber exhibits more CBR, however much high diameter is expected to cause trouble in thorough mixing of fibers into soil mass (Kumar et al., 2015).

2.1 Research Gap There has been many practices to strengthen and stabilize the weak or soft soil since a long duration. Reinforcing natural fibers into soil mass is the most efficient method as it sufficiently increases the bearing capacity of subgrade with involving a very low cost, less human effort and without using any heavy equipment. The recent research approved that use of these natural fibers in appropriate quantity and orientation can be found very effective in significant increase in CBR value. But there is still a doubt to feasibility of these fibers in actual application in subgrade of road pavement. It is very much easy to appropriately mix the fibers in random orientation in soil sample required for conduction of experiment. But when it comes to mixing the fibers in huge heap of weak or soft subgrade mass, there is no proper method to ensure thorough mixing with random orientation.

[107] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) The effect of fibers in the long run is also missing, fibers shows their attractive improvement on bearing capacity of soil immediately but the duration for which subgrade retains these improvement is still has not been studied yet. Natural fibers are bio degradable and may decompose in subgrade mass after a specific duration of time and subgrade might loss its improved bearing capacity, making it unable to withstand the designed load, thus leading to settlement, rutting, potholes and eventually failure of pavement. So it is important to study the long term effect of fibers on strength characteristic of soil.

3. METHODOLOGY Methodology comprises of material collection, sample preparation, conduction of CBR test, cost evaluation, result & discussion over increment of strength of subgrade soil.

3.1 Material Collection and Sample Preparation Locally available soil was collected from VJTI college campus, Mumbai at a depth of 2 meter to ensure that it properly represents the soil properties of local area. Around 4.5 to 5.5kg of soil per sample, passing through 20mm IS sieve and retaining on 4.75mm IS sieve was used. Coir fibers of 0.5mm diameter and 10mm length have been used as reinforcing material. These fibers were procured from a local fiber suppliers in appropriate quantity required for all the specimens. Soil was mixed thoroughly with fibers and water as per optimum moisture content, keeping in mind fibers should be uniformly mixed with discrete random orientation. Reinforced and unreinforced remoulded specimen at proctor’s maximum dry density were prepared by dynamic compaction. The mixed soil was compacted in the mould using heavy compaction i.e. in 5 layers, 56 blows to each layer by 4.89 kg rammer.

Fig. 1: Sample Preparation Total 15 samples were prepared including 3 unreinforced samples and remaining 12 with varying percentage of coir fibers as per below Table 1.

[108] A Sustainable Approach to Subgrade Stabilization using Coir Fiber: Performance and Cost Evaluation

Table 1: Sample Configuration Numbers Sample Fiber Percentage 3 Unreinforced _ _ 3 Reinforced Coir 0.5% 3 Reinforced Coir 0.75% 3 Reinforced Coir 1% 3 Reinforced Coir 1.25%

3.2 CBR Test California bearing ratio (CBR) is an empirical test used mainly to measure the bearing capacity of soil as a subgrade material in the design of pavement. CBR is the ratio of force per unit area required to penetrate a soil mass with standard piston at the rate of 1.25 mm/min to the force per unit area required for the corresponding penetration of a standard material (IITK). CBR test was conducted in accordance with the guidelines provided in IS 2720 part 16 (1987). The test was conducted on all 15 coir fiber reinforced and unreinforced samples. After conducting test on prepared samples, results were evaluated and improvement in strength was assessed which is cited in results and discussion section of this report.

Fig. 2: CBR Equipment and Test Assembly

3.3 Cost Evaluation There are other well-known methods of soil stabilization available such as mechanical compaction, use of geogrid, replacement of soil & chemical stabilization (lime, cement). All these methods provides sufficient strength to soil, therefore we aim to uncover the optimum method of them all, in terms of cost. We considered a 4 lane road stretch of 1000m having depth of subgrade 0.5m and required cost for subgrade stabilization was estimated for three most popular methods viz. fiber reinforced subgrade, conventional rubble soling & soil stabilized with geo synthetic. A deep comparison was undertaken for these methods and most optimum method in terms of cost was proclaimed. Rate analysis was carried out to obtain the cost of coir fiber reinforced subgrade and State Schedule of Rates (SSR) of Maharashtra state for the year [109] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 2018–19 was referred to obtain the cost of soil stabilization using Geogrid and conventional rubble soling. The comparison have been shown in below Table 2. It clearly shows that for stabilization per square meter of a particular stretch of a road, rate of conventional rubble soling is 289 and that of Geogrid is 240, whereas coir fiber costs only 174 Rupees. Hence it can be concluded that use of coir fiber for soil stabilization is optimum method in terms of cost.

Table 2: Cost Comparison of Various Methods of Soil Stabilization Cost of Stabilization of Road Cost of Stabilization of Soil Per Method of Soil Stabilization Stretch of 1km in Rupees sqmt in Rupees Conventional Rubble Soling 23cm Thick 57,80,000 289 Use of Geogrid 48,00,000 240 Use of Coir fiber 0.5m Thick 34,73,600 174

4. RESULTS AND DISCUSSION The result of CBR test on unreinforced sample and samples reinforced with 0.5%, 0.75%, 1% & 1.25% coir fiber have been shown in the below Figure 3 (Graph-Penetration vs Load). Three unreinforced samples were tested for CBR and the average obtained result was 2.859. Three samples reinforced with 0.5% of coir fiber were also tested and the average CBR of three samples was found to be 5.337. Obtained result have shown increment in CBR value by 1.866 times. The average CBR of three samples reinforced with 0.75% of coir fiber was found to be 7.546. The CBR value of these reinforced samples increased by 2.639 times as compared to that of unreinforced sample. The average CBR of three samples reinforced with 1% of coir fiber was found to be 6.857. The CBR value of these reinforced samples increased by 2.398 times as compared to that of unreinforced sample. The average CBR of three samples reinforced with 1.25% coir fiber was found to be 5.936. The CBR value of these reinforced samples increased by 2.3 times as compared to that of unreinforced sample.

Fig. 3: CBR Test Result Graph The results of the CBR tests have been summarized in below Table 3. Results shows that by introduction of coir fiber, CBR value of soil mass can be increased upto 2.64 times. We observed that with increase in quantity of fiber, CBR value also increases with maximum increment at a percentage of 0.75% of coir and then decreasing at 1%. So it can be concluded that 0.75% is the optimum quantity of coir fiber for stabilization of soil. [110] A Sustainable Approach to Subgrade Stabilization using Coir Fiber: Performance and Cost Evaluation

Table 3: CBR Test Result Type of Sample Percentage of Avg. CBR Increment in Percent Increase Increase in CBR Coir Fiber Value CBR Unreinforced _ 2.859 _ _ _ Reinforced 0.5 5.337 2.478 86.67% 1.866 times Reinforced 0.75 7.546 4.687 163.93% 2.639 times Reinforced 1 6.857 3.998 139.84% 2.398 times Reinforced 1.25 5.936 3.077 107.62% 2.076 times

5. CONCLUSION After conducting experiments and studying the effect of coir fiber reinforcement in soft or weak soil, we can conclude that 1. Coir fiber when reinforced thoroughly in random orientation in soil, increases the strength of soil. 2. Strength of soil increases with increase in percentage of coir fibers upto a maximum increase of 2.639 times at optimum quantity of 0.75%. 3. Coir fiber reinforced method of soil stabilization is the optimum method in terms of cost. It is even economical than conventional rubble soling method. 4. Ensuring thorough mixing of coir fibers in soil mass with random orientation is very difficult, it becomes much more problematic when quantity of fibers is high (i.e. more than 1%) and needs extensive research in the same. 5. Fibers with longer length causes trouble in thorough mixing, so researchers suggested that length of fiber should be less than 20mm and quantity should be less than 1%.

REFERENCES [1] Leema Peter, Pk Jayasree, K Balan, Alaka Raj S, “Laboratory Investigation in the Improvement of Subgrade Characteristics of Expansive Soil Stabilized With Coir Waste” 11th TPMDC 2014, Transportation Research Procedia 17 ( 2016 ) 558 – 566, ELSEVIER. [2] Satish Chandra, M. N. Viladkar, and Prashant P. Nagrale, 2015 “Mechanistic Approach for Fiber-Reinforced Flexible Pavements” 10.1061/ASCE0733-947X2008134:115, ASCE. [3] Sayyed Mahdi Hejazi, Mohammad Sheikhzadeh , Sayyed Mahdi Abtahi, Ali Zadhoush, “A simple review of soil reinforcement by using natural and synthetic fibers” Construction and Building Materials 30 (2012) 100–116, 2011, ELSVIER. [4] Anzar Hamid, Huda Shafiq, “Subgrade Soil Stabilization Using Jute Fiber as a Reinforcing Material” Volume 5, Issue 1, ISSN: 2321-9939, 2017 IJEDR. [5] Finu John, Elsa Maria Jose , Manu Varghese, Megha Antu, Megha Joy, “Experimental Study on Improvement of Soil Subgrade Reinforced with Banana and Coir Fibers”, ISSN 2395-00565, volume 5 issue 3,2018, IRJET. [6] Srinivas Rao B., Jayalekshmi S., “Fiber Reinforcement of Soil Sub Grade beneath Flexible Pavements” Indian Geotechnical Conference – 2010, GEOtrendz, December 16–18, 2010, IGS Mumbai Chapter & IIT Bombay. [7] Dharmendra Kumar, Sudhir Nigam, Abhinav Nangia and Shailendra Tiwari, “California Bearing Ratio Variations in Soil Reinforced with Natural Fibers (A Case Study Bhopal Bypass Road)” ISSN No. (Online): 2249-3255, International Journal on Emerging Technologies 6(2): 95-104(2015), IJET. [8] IS code 2720 part 16. [9] http://home.iitk.ac.in/~madhav/expt14.html [10] Schedule of rates 2018-19, Public works Department, Government of Maharashtra.

[111] Suitability of EPS Geofoam in Construction of Road Embankment: Cost and Benefit Analysis

Sarvesh Poredi1 and Sumedh Mhaske2 1 M.Tech. Student, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Associate Professor and HOD, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected], [email protected]

ABSTRACT Construction of road embankments is increasing at a very high rate in India. For embankment filling purpose we generally use earth material or quarrying soil of approved standards which creates imbalance in nature as good quality soil is precious natural resource. Current demand of infrastructure projects is speed construction, sustainability, and ease of construction process. Expanded Polystyrene (EPS) Geofoam blocks are very light-weight fill material which can be used to fill maximum part of embankment with less time without requirement of heavy compaction machinery. Manufacturing process of this man- made material is studied by industrial visit to one of the factory in Taloja, Navi Mumbai. Case study of part of NHAI project of four laning of Panvel-Indapur highway is done and conventional embankment process is compared to EPS Geofoam embankment technique. Aspects such as cost, probable duration of placement rate of EPS blocks, ease of construction, material transportation fuel cost reduction and sustainability for using EPS blocks are analysed and illustrated. EPS Geofoam material was found suitable to use considering its sustainability, properties and ease of construction but not suitable if cost is governing parameter of project. Keywords: Expanded Polystyrene Geofoam, Light-weight Embankment, Sustainable Embankment

1. INTRODUCTION

1.1 General India has second largest road network across the world with about 5.4 million Km. The highway construction has already reached 12,2434 Km during year 2017–2018. The average rate of construction of road is 28 Km per day. This road network is increasing day by day and so is the need for construction of embankments for roads. We usually encounter soft soil such as clay or silt in India and the presence of soft soil increases the cost of stabilization, tedious process and uncertainties in embankment design parameters. These stabilization process are tedious, costly and time consuming. Trending option in various countries like Norway and USA is using light weight fill materials for construction of embankment. One of such material is Expanded Polystyrene Geofoam. It can be possible to design an embankment instead of complete replacement of soft soil or accepting the natural resistance of existing soil using pre-determined properties of EPS Geofoam as it is a man-made material made with standard procedures. Lightweight embankments will reduce the risk of settlement of embankment structure as in conventional embankment there is a heavy load of embankment structure over foundation soil. Cost being a very important factor while selecting an alternative method for any construction project must be considered. Efforts are made to identify some properties of EPS geofoam and its benefits for using it in construction of embankment.

1.2 Objectives of Study The project focuses on comparing probable cost of construction of embankment with conventional method and EPS Geofoam embankment construction method. It also focuses on highlighting properties of EPS [112] Suitability of EPS Geofoam in Construction of Road Embankment: Cost and BenefitAnalysis Geofoam using literature available and state its benefit in various other aspects of construction technology. This is done considering a case study of small patch of Panvel-Indapur four laning of highway. Objectives of the study: ●● To study the process of making EPS Geofoam blocks in India ●● To study various properties of EPS Geofoam which are useful for the construction of road embankment. ●● To generate procedure for construction of EPS Geofoam embankment. ●● To perform cost and benefit in terms of time, quality, ease and sustainability analysis in using EPS Geofoam technology for construction of road embankments.

2. BACKGROUND EPS Geofoam is already being used in countries like USA, Japan, Norway, United Kingdom and Netherlands since 1990’s to encounter the problem of construction of road embankments over soft soil. Some major findings can be stated considering the literature available in form of published research. The primary geosynthetic function provided by the geofoam is compressible inclusion. Using compressible inclusions help in reduction of earth pressure under static and dynamic loading. It can be cost effective for rehabilitating or upgrading the existing structures[12]. In year 2009, deformation based load bearing analysis procedure which utilizes elastic limit stress at 1% strain on EPS geofoam was presented by D. Arellano et al. These procedures consists of maximum vertical stresse from dead load, traffic loads at various levels within EPS fill mass and selecting EPS type that exhibit higher elastic limit stress. Calculation of stresses and strains within EPS mass can allow the selection of lower density for lower stress portion. This can help in cost efficient design of EPS embankment[5]. CBR values interpreted by modified methods given by Xisoodng Huang in 2011 yielded higher values than conventional methods but still less than acceptable soils. By considering the composite actions of concrete slab and geofoam, higher values of resilient modulus and modulus of sub-grade were obtained an approach for selecting appropriate geofoam design para meters was proposed[14]. While considering the construction of North tucker Bridge in downtown St. Louis, Missouri designers were provided with challenge of providing 100-year maintenance free structure. Here the construction material selected was combination of EPS geofoam and soil fill for backfilling. Though the technique was new, placement was done quickly by relatively small crew[3]. Shear strength of EPS geofoam specimen were studied by A. Padade and J. Mandal (2012), increased density of EPS block shows increase in value of cohesion and marginal increase in value of angle of internal friction[9]. Flexural strength of EPS Geofoam increases with increase in density, also cohesion and angle of friction of EPS geofoam increase with increase in density Y.Beju and J. Mandal(2017). The water absorption capacity of EPS geofoam was found very less and it decreased with increase in density[2]. D. Srivastava (2018) suggested EPS geofoam application after observing excessive settlement and distress of approach roads near C-D works of important NHAI project in India. EPS Geofoam was convenient and easy to handle and after six month observation, the pavement quality concrete (PQC) constructed over earthfill material showed sign of distress and cracks but there was no distress or cracks over PQC constructed over EPS geofoam embankment[16]. Geofoam has shown technical feasibility in various projects and various research is still going on regarding its properties study even in India. Cost being a very important criteria for selection of material and technology must be studied and there is a very few literature available that shows cost parameters of using EPS geofoam technology. Not only cost but other benefits of using this technology should be stated.

[113] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 3. EPS GEOFOAM

3.1 Manufacturing of EPS Geofoam EPS Geofoam is being manufactured in India since many years and is also being used in various construction application like podium filling, theatre and amphitheatre seating arrangements, raising the height of floor level without increasing deadload, etc. An industrial visit was done in order to understand the manufacturing process of EPS Geofoam. SIGeofoam industry, Taloja MIDC, Navi Mumbai are one of the the manufacturers of EPS Geofoam blocks. EPS Geofoam is manufactured in five steps.

Fig. 1: Schematic Diagram EPS Geofoam Manufacturing Process (Elragi 2006) First the beads are fed to the tank containing an activist. There is a controlled steam environment present. The density of EPS geofoam block is affirmed at this stage. Length of time for which beads remain in expander and pressure of steam decide the density of final product. Second, storage of pre-expanded beads, called prepuffs, is done. This is a drying stage where open air is used to dry these beads. Third, large silos are used to store this pre-expanded beads then transferred for next steps. This storage allows them to acquire ambient temperature. Condensation of water vapour and the used blowing agent occurs and thus it is called stabilization process. Fourth, The pre-expanded beads are then poured in an available size mould, a 2.4m X 1.2m X 0.6m is mold size used from which approximately 1 Cu.m of block is obtained in SIGeofoam. Longitudinal tiny slots are present in mould from where injection of steam is done, the process of fusion starts here. Even 5-10% of recycled expanded polystyrene are shredded and added with pre-expanded beads or prepuffs. This provokes additional fusion and expansion. The moulded block is thus obtained which is then pushed mechanically and carried to dry place for storage. This process is the block moulding process.

Fig. 2: Silos and Steam Moulding (SIGeofoam 2018) Fig. 3: EPS Geofoam Blocks (SIGeofoam 2018)

[114] Suitability of EPS Geofoam in Construction of Road Embankment: Cost and BenefitAnalysis

3.2 Useful Properties of EPS Geefoam Various physical properties of EPS Geofoam are tabulated ASTM D6817. Mohammad Rafiullah (2016) provided information regarding various properties and application of EPS Geofoam to civil engineering. Few key properties are given below: 1. Density: EPS Geofoam is classified on the basis of its density as it is main index property. Properties of EPS geofoam vary according to the density of the block. EPS blocks are designated using its density number. For example, EPS19 means the block of 19 Kg/Cu.m density. 2. Water Absorption: More is the density, tighter is the packing of EPS material in block. Thus, water absorption decreases with increase in density. It varies from 2 to 4 % which is very less if compared to the soil mass. 3. Weight: EPS Geofoam block is approximately 1% the weight of conventional embankment soil. Which make it the most lightweight manmade filling material which can reduce stresses on underlying soil or structure. 4. Durability: Life of the EPS Geofoam material can be expected from 75–100 years which is very high. 5. Flammability: EPS Geofoam is combustible but it has a self-extinguishing property and care must be taken at the site storage areas and it must not be exposed to flame directly. 6. Resistance: EPS Geofoam is soluble in petroleum and so geo-membrane layer must be put over it if we use it for embankment construction. It has no nutrition value and so ants, termites etc do not attack these blocks after placement in to the soil. 7. Environmental Effects: As studied before 5–10% of recycled material is used and only water and steam is used for manufacturing EPS geofoam blocks. No harmful gases are emitted. It is also chemically inert in water and soil (Hovarth, 1993).

Table 1: Physical Properties of EPS Geofoam (ASTM D6817) Property Unit EPS12 EPS15 EPS19 EPS22 EPS29 EPS39 EPS46 Density, Minimum Kg/m3 11.2 14.4 18.4 21.6 28.8 38.4 45.7 Compressive Resistance @ Kpa 15 25 40 50 75 103 128 1% Deformation, Minimum Compressive Resistance @ Kpa 40 70 110 135 200 276 345 10% Deformation, Minimum Elastic Modulus, Minimum Kpa 1500 2500 4000 5000 7500 10300 12800 Flexural Strength, Minimum Kpa 69 172 207 276 345 414 517 Water Absorption by Total Volume% 4 4 3 3 2 2 2 Immersion, Maximum Buoyancy Force Kg/m3 990 980 980 980 970 960 950

4. CASE STUDY

4.1 General National Highways Authority of India (NHAI) has entrusted the work of design, construction, development, finance, operation and maintenance of Four-Laning of the Panvel - Indapur section of NH-17 (Presently, NH-66) in the state of Maharashtra under NHDP phase - III on DBFOT basis (Package No : NHDP-III/DL4/05) to M/s Supreme Panvel-Indapur Tollways Pvt. Ltd. (SPITPL). The project is of 84.6km length and basically is for 4-laning of existing 2-lane highway project. the chainage 52/000 to 53/000 is

[115] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) selected for cost comparison and time comparison of conventional method adopted for embankment filling and EPS geofoam embankment filling. The reason for selecting this patch of work is that it requires a large amount of embankment fill material. The average filling from the chainage 52/208 to 52/680 is around 2.16m and varies from 0.5m to 3.69m. Road width is 10.5m for construction of two new lanes.

Fig. 4: Road Profile of the 52/000km to 53/000km After calculation of filling requirement it was clear that average embankment filling depth is greater than 0.5m for the patch 52/280 to 56/680 chainage. EPS Geofoam blocks available in market is of size 0.5m depth. So, accordingly sections were divided and calculation of EPS filling and conventional filling was done for comparison.

Table 2: Pavement System Thickness Details Depth Pavement Subgrade Sub-grade Depth of Pavement BC DBM WMM GSB System Conventional EPS Pavement System EPS (m) (m) (m) (m) Conventional (m) (Proposed) (m) Embankment (m) Embankment (m) 0.04 0.085 0.25 0.2 0.5 0.8 0.575 0.875 Quantity of Filling of embankment using conventional method was estimated to 10412 Cu.m and if the same embankment if constructed with EPS Geofoam then quantity of EPS Geofoam required shall be 7875 Cu.m and remaining 2537 Cu.m shall be soil which can be used to place over top layer of 300 mm and bottom layer for making surface horizontal before placement.

Table 3: Total EPS Filling and Conventional Filling Calculation as Per Chainage Distribution Section Depth Depth of Conventional Filling (Cu.m) Chainage (m) (m) EPS(m) Filling (Cu.m) 0.5 to 1.0 210 0.5 52.28, 52.68 386.715 1.0 to 1.5 1050 1 52.3, 52.32, 52.44, 52.46, 52.66 1729.245 1.5 to 2.0 630 1.5 52.42, 52.64 863.205 2.0 to 2.5 2520 2 52.34, 52.4, 52.56, 52.58, 52.6, 52.62 3183.075 2.5 to 3.0 2100 2.5 52.36,52.38 52.48, 52.54 2620.275 3.0 to 3.5 630 3 52.52 790.23 3.5 to 4.0 735 3.5 52.5 839.16 Total Filling EPS 7875 Total Filling for Conventional 10411.905 Embankment Embankment

[116] Suitability of EPS Geofoam in Construction of Road Embankment: Cost and BenefitAnalysis

4.2 Proposed EPS Geofoam Embankment Features The EPS embankment depth will vary from 0.5m to 3.5m for the chainage as given in above table. Material considered for the cost analysis are given below and the step wise procedure that shall be carried out for construction of EPS geofoam embankment is given in short.

Fig. 5: 3-D Cross Section of EPS Geofoam Embankment Pavement System

Source: Alliedfoamtech.com

4.2.1 Important Components 1. EPS Geofoam Blocks: The blocks must bear the properties as specified in AASHTO specification for EPS Geofoam. The blocks are available in EPS19 to EPS39 for construction of embankment but for cost analysis EPS19 is considered for optimisation.

Fig. 6: EPS Geofoam Blocks Placement on Site

Source: www.epsindustry.org 2. HDPE Geomembrane: The main function of this is to keep geofoam away from oil spills or petroleum as EPS geofoam may dissolve in petroleum. These membrane can be of range 200- 500 microns as per the design. 3. Embankment Soil: There should be minimum 300mm soil layer before sub-grade construction as heavy compaction equipment can damage the blocks if placed directly over top layer of EPS geofoam blocks.(NCHRP Report 529) 4. CPRX or RBA Compound: Cold applied rubberised compound or rubberised bituminous adhesive these are harmless non- toxic compounds used to connect EPS geofoam blocks horizontally and vertically. 5. Geo-grippers: To ensure shear resistance between two layers of EPS geofoam blocks in horizontal plane, these galvanised steel plates are placed. They ensure internal friction between blocks they control horizontal and lateral movement of multi-layered EPS Geofoam blocks. (EPS geofoam accessory document, 2011).

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Fig. 7: Geo-gripper Plate

Source: www.universalconstructionfoam.com

4.2.2 Installation Steps 1. Site Preparation: Ideally there should be no water or ice present on the foundation soil. There should be no debris or large boulders or vegetation. Sand layer of thickness 12mm-25mm can be made to ensure horizontal ground profile for placement. 2. Placement of EPS Geofoam Blocks: The blocks must be placed with its thickness oriented vertically. Minimum two block layers is recommended beneath the road. Geogrippers are installed as per design drawings in horizontal plane. CPRX compound is used to connect geofoam blocks vertically. 24 hours setting time is given. Blocks are aligned in such a manner that staggered joint system is generated as given in figure.

Fig. 8: Placement of EPS Blocks in Different Layers

Source: NCHRP Report 529 3. Wrapping of EPS Geofoam blocks with HDPE Geo-membrane is done. 4. Providing Soil Layer Over EPS Embankment: Soil conforming to embankment standards shall be placed with minimum thickness of 300mm over the top layer of EPS geeofoam embankment. Then it is compacted before the sub-grade work starts over it. 5. Side Slopes if Present Shall be Covered with the top Soil or Vegetation Soil Layer. Detailed guidelines can be found in ASTM D7180 and NCHRP report 529.

4.3 Cost Comparison Cost of conventional embankment using traditional method is done using schedule rates 2018-2019 provided by Govt. of Maharashtra Public work department. Cost for excavation of soil, conveying of obtained material, compacting and providing earth work, cost of borrowed soil along with its royalty, GST and transportation cost considering 7.5km lead is evaluated. Overall construction cost for 10412 Cu.m of embankment construction was estimated as Rs. 1,70,59,228.

[118] Suitability of EPS Geofoam in Construction of Road Embankment: Cost and BenefitAnalysis After performing rate analysis considering EPS embankment with 100m length and 10 m width and 1m thickness of EPS19, unit cost of EPS geofoam per Cu.m was generated. Cost of providing and fitting EPS19 geofoam embankment along with HDPE geomembrane 200-500 micron and spot CPRX or RBA adhesive provision to connect blocks vertically and providing geo-grippers as per design came out to be Rs. 3493.32 per Cu.m. Total cost for construction of EPS Geofoam embankment along with placement of soil came out to be Rs. 2,86,92,390.

4.4 Fuel Cost Reduction EPS Geofoam is a very lightweight material so it is easier to transport the prepared block from factories and stored on site even before actual construction occurs. Loading in to the trucks is easier as it can be done by lifting blocks by humans itself without use of heavy machinery which consumes fuel. Also, unlike the dumpers which are used to transport the soil from one place to another, here flat-bed trucks can be used. Maximum capacity of one dumper can be considered as 6 Cu.m for soil transportation. According to the NCHRP 529 Report one flat bed truck can carry 50 to 100 Cu.m of EPS geofoam to the site. For example consider the above case study,For transporting 7875 Cu.m of soil, no of load trucks with 6 Cu.m capacity will be 1312.5 say 1313 Nos. While for the same quantity of EPS Geofoam transported using flat bed truck considering capacity 50 Cu.m, we will require 157.5 say 158 Nos.

4.5 Time Analysis using Past Experiences Ease of placement of EPS geofoam on site is its prime advantage over the conventional soil embankment filling method. It requires no compaction process. As there is no past experience of construction of embankment using EPS geofoam we can find no case studies from India but EPS geofoam is being used in USA since a very long time and we can use that data in order to predict the rate of placement of EPS geofoam for embankment construction. This data is made available in NCHRP Report 529.

Table 4: Placement Rate of EPS Geofoam Embankment Place Project Quantity Placement Rate of EPS Blocks Per Day Indiana Reconstruction of state route 4708 428 109, Noble county New York State route 23A, Town of 3155 382 Jewett, Greene County Illinois 4 lane state roadway project 15291 313 in Orland Park

5. RESULTS AND DISCUSSION

5.1 Results

5.1.1 Cost Comparison Result The estimated cost of EPS geofoam embankment construction for considered case study is 1.68 times more than the cost of conventional.

[119] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 5.1.2 Fuel Cost Reduction Result Reduction in number of truck load of material for using EPS Geofoam use in case study considered was 1155 Nos. If compared with conventional soil transport this reduction is about 8.31 times. This will reduce the fuel cost for transportation of material on site.

5.1.3 Placement Rate of EPS Geofoam Embankment From the case studies in Indiana, New York & Illinois it can be clearly seen that placement rate of EPS Geofoam block in embankment construction is greater than 300 Cu.m per day in all the three cases.

5.2 Discussion ●● For manufacturing EPS Geofoam blocks, styrene monomer and water is used. The only gas that is emitted is water vapour. No harmful by products are obtained. Also, recycled expanded polystyrene [5 to 10 %] are used for manufacturing EPS block. Thus, it follows sustainable approach for manufacturing EPS Geofoam blocks. ●● Properties of EPS Geofoam and its cost depend upon the density of the Geofoam block. Being a man-made material it properties can be pre-defined which provides a helping hand for designing an embankment with confidence. ●● Low water absorption, low density & light weight material with good compressive strength are key properties of EPS geofoam blocks which prove its suitability in construction of embankment over soft soil. ●● Cost of construction of EPS geofoam embankment is higher than conventional soil embankment as unit cost of material is higher. But, if soft soil case study is considered we can not deny the fact that the cost difference will reduce substantially. ●● The placement rate of EPS geofoam blocks is greater than 300Cu.m per day, but it may vary according to site conditions of road project. ●● There can be great reduction in fuel cost for transportation of embankment material which indirectly will reduce carbon emission from the consumption of fuel and even the transportation cost of embankment construction. ●● Soil is a precious natural resource which is formed naturally after weathering of rocks for several thousands of years and so it must be used wisely. EPS geofoam is man-made material and can substitute major part of it in embankment construction.

6. CONCLUSIONS Looking towards the success rate in using EPS Geofoam in construction of embankment in various countries it can be stated that this lightweight man-made material can be used in construction of embankment. The cost evaluated in this report states that cost of EPS geofoam in construction of embankment is more than conventional embankment construction. This material can be considered as a sustainable material due to high life,no environmental hazards and reusability and so it has advantages over conventional soil fill material thus, in future it can be considered as sustainable embankment construction approach. This material being light-weight can be transported on site with very less cost and can be placed on site with low labor and no heavy machineries saving construction cost. Thus looking towards other benefits higher cost can be acceptable for fast track projects. Also this technology is new in India, and material cost obtained from market survey can surely reduce if bid system is adopted in future for construction of embankment using EPS geofoam. In order to facilitate sustainability and speed development of road network in India, such new technology and material must be given a try. The properties of man-made [120] Suitability of EPS Geofoam in Construction of Road Embankment: Cost and BenefitAnalysis are well defined and can help designers to design the embankment with minimum uncertainties. Not only cost, but time required of construction and uniform quality of EPS geofoam material must be given weightage while considering its use in embankment construction.

REFERENCES [1] Mohammad Rafiullah, Diwan Usama (2016), “Geofoam construction and application to industry”, International Journal of Recent Advances in Engineering & Technology (IJRAET), Vol. 4, Issue 3, pp. 64-69. [2] Y.Z. Beju and J.N. Mandal (2017), “Expanded polystyrene (EPS) geofoam: preliminary characteristic evaluation”, Transportation Geotechnics and Geoecology, TGG 2017, 17-19 May 2017,Elsevier Procedia Engineering 189, pp. 239– 246. [3] J. Anderson, P. Poepsel and K. Kriete (2013), “Design and Construction of Freestanding Expanded Polystyrene RoadwayEmbankment in Downtown St. Louis, Missouri”, Geo-congress 2013, ASCE 2013, pp. 1429-1445. [4] John S. Horvath (2010), “Emerging Trends in Failures Involving EPS-Block Geofoam Fills”, Journal of Performance of Constructed Facilities, ASCE / July/August 2010, pp. 24:365-372. [5] D. Arellano and T.D. Stark (2009), “Load bearing analysis of EPS-block geofoam embankments”, Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) 2009 Taylor & Francis Group, London, ISBN, pp. 981-990. [6] Marradi A, Pinori U, Betti G (2012), “The use of lightweight materials in road embankment construction”, Procedia -Social and Behavioral Sciences 53 (2012), Elsevier, pp. 1001–1010. [7] Stark, T. D., Arellano, D., Horvath, J. S. and Leshchinsky, (2004), “Guideline and recommended standard for geofoam applications in highway embankments.” NCHRP Rep. No. 529, TRB, Washington, D.C. [8] Abbas Mohajerani , Matthew Ashdown, Luqmaan Abdihashi, Majidreza Nazem (2017), “Expanded polystyrene geofoam in pavement construction”, Construction and Building Materials 157, Elsevier, pp.438-448. [9] B.S. Asha, B. Ram Rathan Lal, A. H. Padade, T. Mandal and J. N. Mandal (2012), “Emerging Trends in Ground Improvement Techniques”, GeoCongress 2012, ASCE, pp. 594-603. [10] Amit Harihar Padade and J. N. Mandal (2012), “Behavior of expanded polystyrene (EPS) Geofoam under triaxial loading conditions”, Electronic Journal of Geotechnical Engineering vol. 3. September 2012, Researchgate, pp. 2543-2553. [11] Gao, H., Chen, G. and Wang, Z. (2012) “The Mechanical Behaviors of the Embankment Filled with EPS Composite soils,” Advanced Material Research Vols, Switzerland, pp. 2813-2818. [12] Horvath, J. S. (1997) “The compressible inclusion function of EPS Geofoam,” Geotextiles and Geomembranes, Elsevier: pp. 77-120. [13] Lee-Kuo Lin; Li-Hsien Chen; and Roger H. L. Chen (2010) “Evaluation of Geofoam as a Geotechnical Construction Material”, Journal of materials in civil engineering, ASCE, pp.160-170. [14] Xiaoodng Huang and Dawit Negussey (2011), “EPS Geofoam Design Parameters for Pavement Structures”, Geo-Frontiers 2011, ASCE, pp. 4544-4554. [15] T. Stark, D. Arellano, J. Horvath and D. Leshchinsky (2005), “Guidelines and Recommended Standard for Geofoam Application in Highway Embankments”, NCHRP Report 529.

[121] Integrated Water Resources Management in Kosi Basin

Dr. Rajesh Gupta Reader, WALMI, Patna, Bihar, India E-mail: [email protected]/ [email protected]

ABSTRACT For planning, development, conservation, and management of water, land, forest, and aquatic resources in a river basin context and to maximize economic benefits and social welfare in an equitable manner without compromising the sustainability of vital environmental system a new concept has been widely used known as Integrated Water Resource Management (IWRM). In IWRM we have to incorporate participatory decision-making. The area of North Bihar is about 5.4 million hectares, where 8 major rivers are Gandak, Burhi Gandak, Adhwara group of rivers, Bagmati, Kamla, Bhutahi Balan, Kosi and Mahananda. In North Bihar 76 per cent of the land is flood affected. As per state government’s report, approximately 0.8 million hectares of land is waterlogged every year, 15 % of agricultural land is rendered useless affecting livelihood of 6 million people. The above issues for Kosi basin has been described and discussed in detail.

1. INTRODUCTION It is strange that in our effort to make the mother earth yield more for ourselves, we are diminishing our water resources. Forest cover which stabilizes the climate, helps in maintaining flow in water bodies as recharging of ground water, preserve flora & fauna and protects majority of the planet’s biodiversity is shrinking in the process of industrialization & urbanization. Unregulated multiple uses of river water in various segments of consumption have caused serious problems to the water bodied. It is important that some sort of rationale is arrived at to maintain a balance and sustain the flow in water bodied and flows down the process of depletion of ground water table. Govt. of India, Ministry of Environment and Forest has framed an act (water cess act) whereby an industry has to pay cess (tax) for consummation of water used in industrial production and other consummation such as in their colony etc. Water cess act is also applicable to civic bodies also such as municipal corporation, municipalities military cantonment etc. But civic bodies normally do not comply this. This act can be a good tool to rationalize the domestic consumption. Water is a scare commodity, since the utilizable water resources on the earth surface cannot be expanded to meet the increasing needs of agricultural, domestic, industrial and environmental sectors. The state is divided into 38 districts and 533 community development blocks. Bihar is state with plenty of water resources. Besides having huge water resources, the per capita income in Bihar low when compared to many states in the country. Using the vast resources of water as sustainable source for drinking, industrial and irrigational purposes, overall development of the vast population of the state can be improved to a great extent. Bihar is the most flood-prone state of India. 16.5 percent of the total flood-risk area of the country and 22.1 percent of the flood-risk population in India lives in Bihar. About 73 percent of the state’s total geographical area is at risk from perennial floods. Recurrent floods account for thousands of human lives and livestock and have wiped out assets worth millions. In addition, the region is falls in seismic Zone IV and V. In this paper IWRM and above issues for Kosi basin has been described and discussed in detail.

[122] Integrated Water Resources Management in Kosi Basin 2. INTEGRATED WATER RESOURCES MANAGEMENT (IWRM) Integrated water resources management is a logical concept. Many different uses of water resources are interdependent. That is evident to us all. High irrigation demands and polluted drainage flows from agriculture mean less freshwater for drinking or industrial use, contaminated municipal and industrial wastewater pollutes rivers and threatens ecosystems, if water has to be left in a river to protect fisheries and ecosystems, less can be diverted to grow crops. When responsibility for drinking water rests with one agency, for irrigation water with another and for the environment with yet another, lack of cross-sectoral linkages leads to uncoordinated water resource development and management, resulting in conflict, waste and unsustainable systems as shown in Fig -1.

Policy and legal Integrated management framework

Management instruments

Water Infrastructure Supply and Water & Water & Water for Wastewater Agriculture Environme other nt uses

Institutional framework

Fig. 1: IWRM and its Linkage to the Sub-Sectors (GWP, 2004)

2.1 Use of Water ●● We need water to maintain terrestrial and aquatic ecosystems and their functioning, plants evaporate and transpire water, animals drink water, fish and amphibians need water to live in. Water is also used by upper-watershed, like forests, shrub lands and woodlands. ●● Downstream-watershed, like wetlands, floodplains, and mangroves need freshwater inputs. This water is used to maintain a natural dynamic, often of a seasonal nature. To prevent degradation and destruction of ecosystems, it is important to have enough water of the right quality and with the right seasonal variability.

2.2 Importance of Environment ●● For benefit the people and their livelihoods ecosystems provide goods and services. Destruction of the ecosystems penalises the poor most. They benefit from the “free” common resources (fuel wood, water, fisheries, fruits etc). They also contribute to ecosystem degradation through over-exploitation. So, it is important that user communities are involved in water management decisions.

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2.3 Effects on Environment by Water Use in Other Sectors The water for the environment, are neglected in considerations of water allocations. But if too much water is allocated for other sectors, the impacts on ecosystems can be devastating. ●● The agriculture sector is most important as a user of water and impacts most heavily on ecosystems. Abstraction of water for agriculture is leading to dried up rivers, falling ground water tables, salinated soil and polluted waterways. Carefully considered multipurpose projects can combine irrigation with aquifer recharge, land drainage and ecosystem sustenance. ●● Urban water wastewater effluents pollute downstream ecosystems if not sufficiently treated. The treatment of effluents is also very costly. ●● The hydropower affects downstream ecosystems by changing the water and sediment regime and blocking migratory movements of fish and amphibians upstream. Combining considerations of power generation, flood control and ecosystem protection can mean new operational rules for reservoir releases. ●● Industry also has substantial impacts on ecosystems downstream through water use and pollution. Transfer of recycling technologies from developing countries help to check ecosystem damage from industrial development.

2.4 Impact of the Environment on Water Use by Other Sectors ●● Water assigned for ecosystem protection is not available for other uses. The environment can be seen as a competitor by other users. So we should encouraging multiple use and reuse. ●● Well functioning ecosystems provide benefits downstream, such as flood attenuation by a floodplain wetland, or the cleansing of limited amounts of pollution. ●● Ecosystems maintained in a healthy state can provide good quality water that can be used by any other user.

2.5 Benefits of IWRM to the Environmental Sector ●● By applying an integrated approach to water management and giving environmental needs a voice in the water allocation debate, at present these needs are often not represented at the negotiating table. ●● IWRM can help by raising awareness among other users of the needs of ecosystems and the benefits these generate for them. Often these are undervalued and not incorporated into planning and decision-making. ●● IWRM focuses more attention on a system approach to water management. It provides more emphasis on maintaining the underlying ecosystem as a factor that can join stakeholders in developing a shared view and joint action. ●● An ecosystem approach to water management focuses on several field level interventions such as protecting upper catchments (e.g. reforestation, good land husbandry, soil erosion control etc..), pollution control and environmental flows (e.g. special releases from reservoirs for river restoration). ●● The IWRM concept can bring together communities, industrialists, water managers and opinion formers (teachers, religious leaders, media representatives) in a common cause to achieve sustainability by conserving both water and ecosystems.

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2.6 Barriers to Implementing IWRM in the Environmental Sector Of all the sectors, the environment is probably the one with most to gain from implementation of IWRM. Usually at the end of the queue when water allocations are made, it is suffering the consequences of water scarcity and poor awareness. The desire for an IWRM approach is therefore very strong in the environment sector, but there are some stumbling blocks to be overcome:

●● Lack of awareness among all water users is the biggest obstacle to change. Especially in the developing world, the impacts of poor water management are only just starting to be noted. Floods, pollution and depleted rivers are beginning to get a bit more public attention, but freshwater biodiversity is still outside the sphere of interest of most people. ●● Lack of political will to combat vested interests is also an important barrier. Fishes have no voice, farmers do. ●● Lack of human and financial resources causes ecosystems not to be taken into account in planning and development. A lack of capacity in government agencies and an overall lack of financial resources to invest in sustainable practices.

2.7 Implications for Change with in the Environmental Sector: Legal, Institutional, Human Resources From the environmental perspective, a major requirement of water sector reform is to provide recognition of ecosystem needs alongside the demands of domestic, industrial and agricultural water users. ●● National legislation often needs to be harmonised and strengthened to include an environmental perspective into water management and other relevant sectoral policies and legal arrangements. At present many conflicting arrangements exist. ●● Participatory decision-making is a crucial part of IWRM, but it has to be in a framework that protects common interest from self interest. It is the role of government to set and maintain standards that prevent upstream users from depleting or degrading the water resources of downstream users. ●● The above requires a substantive capacity building in facilitation, mediation, negotiation and surveillance. At present, staffs are often not well equipped to take on these responsibilities as they require knowledge and skills beyond those traditionally taught to an engineer or hydrologist.

2.8 Use of Water in Agricultural Sector Without water there is no food production. Water is used for crop production, livestock husbandry and aquaculture. Crops (Table 1) ●● Crops grow best and produce most when they have an adequate supply of water available to them. Water is mainly used for transpiration and smaller amounts are stored in plant tissues. ●● Sources of water for crop production are rainfall, shallow groundwater and irrigation water, which is diverted from surface flows or groundwater. ●● Crops rely on residual moisture stored in the soil. As well as the usual irrigation water sources, water harvesting is increasingly becoming an important source of water for agriculture.

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Table 1: Total Amount of Water Needed to Produce a Kg of Some Staple Crops and Soybean Oil

Production of 1 kg of : Water Required (m3)

Wheat 1.3 Rice 3.0 Soybean oil 22

Source: FAO (1997), Waterhouse (1982) – note this is not the amount transpired, but the total required for production Livestock (Table 2) ●● Like humans, animals need water for their metabolic processes. Water requirements for livestock are direct water intake and partly by the moisture content of their forage. ●● When livestock does not have access to grazing pastures or where forage cannot be grown under rainfed conditions, fodder is grown by irrigation. Then production of forage requires substantial amounts of water.

Table 2: Estimates of Livestock Water Requirements Type of Animal Water Consumption (Litres/Day/Animal)

Dairy cows (drinking only) 40–50 Beef cattle and steers 45–55 Horses in pasture 28 Horses at work 45–55 Pigs 14–18 Goats 10 Sheep 6–9 Chickens 0.25–0.5

Source: Waterhouse, J. (1982)

2.9 Benefits of IWRM to the Agricultural Sector Agriculture is the single largest user of water and the major non-point source polluter of surface and groundwater resources, agriculture has a poor image. Indiscriminate reduction in water allocation for agriculture may have far-reaching economic and social consequences. With IWRM, planners are encouraged to look beyond the sector economics and take account of the implications of water management decisions on employment, the environment and social equity. ●● IWRM helps into the decision-making process by bringing all sectors and all stakeholders, and reflect the combined “value” of water to society as a whole in difficult decisions on water allocations. This causes the contribution of food production to health, poverty reduction and gender equity. There is a strict economic comparison of rates of return on each cubic metre of water. IWRM can bring the reuse potential of agricultural return flows for other sectors and the scope for agricultural reuse of municipal and industrial wastewaters. ●● IWRM calls for integrated planning so that water, land and other resources are utilised in a sustainable manner. For the agricultural sector IWRM seeks to increase water productivity (i.e. more crops per drop) within the constraints imposed by the economic, social and ecological context of a particular region or country. A major shift in focus under IWRM is the concept of demand management (i.e. managing water demand rather than simply looking for ways to increase supply).

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2.10 Barriers to Implementing IWRM in the Agricultural Sector Successful IWRM requires consideration of a wide range of social, economic and political issues at a variety of different scales. Barriers to successful implementation of IWRM within the agricultural sector include: ●● Incompleteness in water management policy and legal and regulatory frameworks. ●● Demographic pressures. ●● Lack of understanding of IWRM principles and practices. ●● Inadequate information and data of water used in agriculture. ●● Lack of understanding of the inter-relationships between biophysical and socio-economic aspects of a system.

3. USE OF WATER IN WATER SUPPLY AND SANITATION SECTOR The water supply and sanitation sector has two main categories of water users such as domestic and industrial/commercial. The quantities of water used for domestic water supply and sanitation are relatively small compared with water use for industry or agriculture. Domestic water users required dependable supplies of “safe” water for drinking, cooking, bathing, washing and basic household cleaning and to dispose of human waste and wash water which do not create health risks or environmental damage. Industrial users frequently need large quantities of water for cooling and other processes, but do not “consume” much of it. Their residual water is returned, often in contaminated form to water courses. Some industries such as chemicals, fertilisers, coffee processing, etc. produce highly toxic or biologically polluting effluents. Industrial water use varies from industry to industry and from country to country. Among the biggest water consumers are the pulp and paper industry and steel manufacture. Two more factors distinguish domestic water supplies from those in other sectors: quality and reliability.

3.1 Importance of Water Supply and Sanitation

3.1.1 Water is a Basic Human Right Without safe and sufficient drinking water and sanitation, people cannot live healthy and productive lives. Water is firstly crucial to keep the human organism alive and healthy. Domestic water is also critical for waste disposal – through sewers or into septic tanks or latrines. All of these uses, as well as small quantities for cooking and cleaning/washing are so essential to human well-being that they are universally acknowledged as being both a need and a right. There is an increasing recognition of the important role in economic well-being and poverty reduction that a supply of water for productive use can provide at the household level. It has been argued that because of the range of economic and social benefits, including income generation, food security, and improved nutritional status this additional quantity of water should be included with the core domestic requirement as a key priority and right in water resource allocation.

3.1.2 Gender Equity Lack of convenient access to water and sanitation adds enormously to women’s domestic burdens. It also disproportionately affects their health and that of their children.

[127] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 4. KOSI RIVER BASIN The salient features of the Kosi basin are as described below:

4.1 Land Use The total geographical area of the basin is 11,41,019 ha. The land use pattern as per 1991 report is as indicated below in Table-3:

Table 3: Land Use in Kosi Basin Sl. No. Category Area in ha Percentage of Total Area 1 Forest land 3,297 0.30 2 Land under Misc trees & groves 34,332 3.01 Current fallow 90,052 3 Other fallow 31,753 1,28,891 11.30 Culturable waste 7,086 4 Net area under cultivation 7,09,209 62.15 5 Barren land and permanent pastures 79,257 6.94 6 Area under non-agricultural use 16.30 1,86,033 Total 11,41,019 100.00

4.2 Forest Cover The present forest cover is only 0.30 per cent of the basin area. Adding to it the area of 34,332 ha under miscellaneous trees and groves, the percentage rises to 3.31. This is much less than the minimum requirement of 33 per cent considered necessary for maintenance of ecological balance and environmental protection. The current fallow, other fallow, culturable waste, barren land and permanent pastures in the basin cover vast area of 2,08,148 ha which is 18.24 per cent of the basin area. This provides good scope for increasing the forest cover.

4.3 Cultivable Land At present the net area under cultivation is reported as 7,09,209 ha. Adding to it the current fallow of 90,052 ha, the total cultivable land comes to 7,99,261 ha, which is 70.0 per cent of the basin area.

4.4 Present Cropping Pattern The present cropping pattern in the basin is as given in Table 4:

Table 4: Present cropping Pattern in Kosi Basin Percentage of Net Sown Area Sl. No. Crop Seasons Irrigated Rainfed Total 1 Bhadai (Early Kharif) 0.14 2.02 2.16 2 Kharif 17.79 43.80 61.59 3 Rabi 32.81 14.11 46.92 4 Hot weather 12.71 32.89 45.60 5 Annual crop (sugarcane) 0.05 0.36 0.41 Total 63.50 93.18 156.68

[128] Integrated Water Resources Management in Kosi Basin The main kharif crop is paddy but some maize, millets, pulses, oilseed and vegetables are also grown in some areas. Wheat, boro paddy and winter maize are the main crop of Rabi but the coverage is small due to lack of irrigation facilities. Paddy, maize and vegetables are the main Hot Weather (HW) or Garma crops which are mostly grown in the basin. The above table indicates that while intensity of cultivation is 156.68 per cent the intensity of irrigation is 63.50 per cent of the area presently under cultivation.

4.5 Water Resources of the Basin

4.5.1 Surface Water 1. Availability at Barrage site at Bhimnagar 47,065 MCM 2. Available from basin’s own yield 5,154 MCM Total 52,219 MCM Ground Water: Annually replenishable and utilizable ground water potential of the basin is 3700 MCM. Hence total availability of water in the basin is 1. Surface Water 52,219 MCM 2. Ground Water 3,700 MCM Total 55,919 MCM

4.6 Inter Basin Transfer of Water Almost entire command area (88 per cent) of the western Kosi canal falls in the Kamla basin. Only 12 per cent of command area falls on the right bank of the Kosi. The quantity of water to be utilized has been assessed as about 1368 MCM. The crop season wise breakup of the utilization of Kosi water in Kamla basin is assessed as follows: Kharif 627 MCM Rabi 394 MCM HW & Annual 347 MCM 1368 MCM

4.7 Net Quantity of Water Available for Agricultural Use in the Basin Deducting the amount of water set apart for domestic and industrial uses and transfer to the other basin in the state, the net quantity of water available for irrigation in agriculture may be as follows: 1. Surface water Total availability 52,219 MCM Deductions a. Amount set apart for the release to Nepal - (–) 541 MCM b. Amount for the domestic and industrial uses taking 15 per cent of the surface water available below Kosi Barrage (5154 MCM) (–) 773 MCM c. water proposed to be transferred to Kamla basin (–) 1,368 MCM Net Quantity Available 49,537.00 MCM [129] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

4.8 Prospective Cropping Pattern in the Basin The basin area is covered by Saharsa, Madhepura, Purnia and Katihar districts having normal annual rainfall as 1287.9, 1230.5, 1727.5 and 1297.8 mm respectively. The important crops of the basin are paddy, jute, sugarcane, maize and mustard. The usual crop rotations followed in the basin are the following: a. Paddy – Wheat/Barley b. Jute – Barley/Wheat c. Maize – Barley/Wheat/Mustard d. Paddy – Wheat- Green Gram (Moong) e. Paddy – Winter paddy –Green Gram (Moong) f. Maize – Wheat/Potato/ Green Gram (Moong) g. Paddy – Sugarcane. This basin has a large number of depressions in the form of chaurs where water stagnates during kharif and only boro paddy is raised. Winter rice is a promising crop and so is the case of winter maize. Cultivation of moong and urad (black gram) in summer has established. The sugar and jute industries of the basin have to be sustained and developed.

Table 5: Cropping Intensity in Kosi Basin Percentage of Cultivable Area Crop Seasons Rainfed Irrigated 1. Kharif a. Bhadai – 20 b. Agahani 26 40 Sub Total 26 60 2. Rabi 12 58 3. Hot weather 5 35 4. Annual – 9 Grand Total 43 162

4.9 Consumption of Irrigation Water With the above cropping pattern the consumption of irrigation water has been assessed in two parts i.e. (i) within the Kosi command and (ii) outside the Kosi command including high patches within the command as shown in Table-6.

Table 6: Water Consumption in Kosi Basin (Unit: MCM) Within Project Total (As Per Prospective Seasons Outside Command Command Cropping Pattern of the Basin) 1. Kharif Surface Water 1980 981 2961 Ground Water – – – 2. Rabi Surface Water 1480 142 1622 Ground Water – 800 800 3. Hot Weather and Annual Surface Water 1327 – 1327 Ground Water – 844 844

Table 6 (Contd.)...

[130] Integrated Water Resources Management in Kosi Basin

...Table 6 (Contd.)

Within Project Total (As Per Prospective Seasons Outside Command Command Cropping Pattern of the Basin) Total Surface Water 4787 1123 5910 Total Ground Water – 1644 1644 Total (GWW + SW) 7554

4.10 Sources for Supply of Irrigation Water 1. There is one existing major schemes in the basin. This scheme is expected to provide irrigation water during different crop seasons in quantities as mentioned below: Kharif – 1980 MCM Rabi 1480 MCM Hot Weather & Annual – 1327 MCM Total 4787 MCM Hence overall utilization of water resources will be as below: Surface Water 1. Municipal & Industrial uses 773.0 MCM (1.48%) 2. Irrigational use a. Major & Medium schemes 4,787.0 MCM (9.17%) b. Minor Irrigation Schemes 1,123.0 MCM (2.15%) c. Transfer to Kamla basin 1,368.0 MCM (2.62%) d. Release to Nepal 541.0 MCM (1.03%) Subtotal 8,592.0 MCM (16.45%) 3. Release into River 43,627.0 MCM (83.55%) Total 52,219.0 MCM (100%) Ground Water 1. Municipal & Industrial uses 555.0 MCM (15.00%) 2. Irrigational uses 1,644.0 MCM (44.43%) Balance left 1,501.0 MCM (40.57%) Total 3,700.0 MCM (100%)

4.11 Irrigation Potential of the Basin With the pattern of utilization of surface and ground water for irrigation as discussed above the annual irrigation potential of the basin works out as below: 1. From Major and Medium Schemes Kharif 3,04,700 ha Rabi 2,69,154 ha Hot weather and annual 2,04,186 ha

[131] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Subtotal 7,78,040 ha 2. Minor Irrigation Schemes a. Surface Water Kharif 1,50,923 ha Rabi 25,818 ha b. Ground Water Rabi 1,45,454 ha Hot weather and annual 1,29,846 ha Subtotal (a + b) 4,52,041 ha Grand Total (i + ii) 12,30,081 ha With the above irrigation potential the production of food grain in the basin is likely to be of the order of 31.36 Lakh MT against the requirement of 24.52 Lakh MT for the projected population of 137.11 Lakh by 2025 AD (Second Bihar State Irrigation Commission Report, 1994).

5. KOSI RIVER HYDROLOGY AND ITS CATCHMENT River Kosi originates at an altitude of over 7000 m above mean sea level. The upper catchment of the river system lies in southern Tibet and eastern Nepal in mountainous terrain. Mount Everest and the Kanchenjunga are in Kosi’s catchment. The river is known as Sapta Kosi in Nepal. It enters India near Hanuman Nagar in Nepal. It drains into River Ganga in the Katihar district of Bihar. It drains the catchment of 74,030 sq. km, of which only 11,410 sq. km lies in India. The catchment has an average annual rainfall of 1456 mm. The Kosi has a total length of 260 km in Bihar. Its main tributaries are Bagmati, Kamla Balan, Bhutahi Balan, Trijuga, Fariani Dhar and Dhemama Dhar. The Kosi Barrage with earth dams across river, afflux bunds and embankments above and below the river confines the river to flow within embankments. Embankments on both sides downstream of the barrage with a length of 246 km have been constructed to check the westward movement of the river. The embankments have been kept wide apart, about 12 to 16 km, to serve as a silt trap. Despite the additions in the total length of embankments, Bihar remains one of the most flood-prone states in India and has the highest number of flood-affected people per capita.

6. CAUSES OF RECURRENT FLOODING IN BIHAR The Kosi River is one of the main reasons for the recurrent floods in Bihar. When the water level rises too high, the sluice gates of the Kosi Barrage are opens to protect the structures. This leads to flooding and water-logging in the Gangetic plains of Bihar. The large amount of water discharged from Nepal through Kosi Barrage mainly reaches the Bagmati, Budhi Gandak and Ganga rivers, causing them to break the banks and over flow. In addition, this also carries enormous amounts of sandy silt that gets deposited over arable land and renders it fallow. The following reasons contribute to and exacerbate the flood risk profile of Bihar.

7. CONCLUSIONS Reallocation of water among competing uses is rapidly becoming a common challenge in the region. This impacts most on the poor who are insufficiently empowered to claim water rights. For this we encourage adopting participatory and negotiated approaches for water allocation. It will support the evolution of water allocation through markets of transferable water rights once the necessary policy, legal, and institutional

[132] Integrated Water Resources Management in Kosi Basin frameworks for the IWRM in a river basin context has to be put in place. Regulatory agencies will be helped to develop water rights in a manner that protects the rights of the poor to equitable water services. Important causes of recurrent floods in Bihar, Specially in Kosi basin are lack of upstream disaster risk management and flood management measures like upkeep of embankments, deforestation and regulation constraints of Farrakha barrage etc.

REFERENCES [1] Bihar State 2nd Irrigation Commission Report,(1994),’Outline of the Development and management of Water Resources of Different River basins of Bihar’, Vol. 3, pp. 127-133. [2] ADB, (2000) ‘Basin Planning & management, Water For All’. The Water Policy of Asian Development Bank. [3] TAC Background Papers, no 4, (2000), ‘Integrated Water Resources Management’, ‘Global Water Partnership. 2000.

[133] Laboratory Analysis of Bagasse Ash and Coir Fiber Composite Concrete Blocks for Low Cost Housing

Abhishek Arvind Bane1 and Dr. Sumedh Mhaske2 1M.Tech. (Construction Management) Scholar, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Associate Professor and HOD, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: 1aabane_m17@ ci.vjti.ac.in, [email protected]

ABSTRACT In low cost housing projects, construction materials which are locally available, environment-friendly and cost-efficient play a crucial role. Low cost housing projects are usually located in rural and hilly areas. In such locations to achieve construction cost reduction, walls constructed with blocks made from locally available materials and having enough compressive strength to carry roofing loads can stand as a most suited option. In this paper, an attempt is made to develop the composite concrete blocks made from cement, sugarcane bagasse ash, coir fibre, sand and coarse aggregate. To achieve cost reduction cement is partly replaced by Sugarcane Bagasse Ash and to attain strength and improve bonding coir fibre is added along with other materials. Detailed laboratory tests are carried out on composite concrete blocks to determine the effect of partial replacement of cement with sugarcane bagasse ash on their properties such as compressive strength and block density. Keywords: Low Cost Housing, Sugarcane Bagasse Ash, Coir Fibre, Composite Concrete Blocks

1. INTRODUCTION The housing shortage at the beginning of the 12th five-year plan (2012-2017) is estimated at 18.78 million. The Government of India has set a target of building 20 million affordable houses by 31 March 2022[3]. Conventional construction techniques and materials will not solely be able to fulfil this need and this will create a huge demand for construction materials such as bricks, cement etc. The focus is to be made to identify various construction material alternatives that can potentially provide a reduction in initial construction cost and time as well as to bring sustainability. Low cost housing refers to those housing units that are affordable by the sections of the society whose income is below than median household income [2]. Sustainable housing is the structure which is cost, energy efficient and constructed with locally available, environment-friendly and recycled material, while at the same time being safe. Low Cost Housing does not involve low quality material or sub-standard work but it is the collaborative efforts of effective budgeting, proper management of available resources and reduction of waste. To fulfil the target of building 20 million houses by the year of 2022 there is great need to look for sustainable material alternatives which shall be cheap, locally available, environment-friendly and having satisfactory structural quality in terms of strength, durability etc. The number of researches has been carried out by using unconventional building materials. Various materials such as carbon fibre, glass fibre, polyester, alloys of different metals, Kevlar looked upon as construction materials. However, such type of materials involves a complex manufacturing process and results in an increase in costs. To resolve this issue, it is necessary to formulate the guidelines and to develop technologies that will include locally available materials effectively in Low Cost Housing at the village level itself. [134] Laboratory Analysis of Bagasse Ash and Coir Fiber Composite Concrete Blocks for Low Cost Housing 2. LOW COST HOUSING MATERIALS Materials such as earth, bamboo, fly ash and natural fibre exhibits excellent properties. But due to lack of codal guidelines, technology transfer and manufacturing facilities associated with these materials hinder their application in the construction process [7]. Natural fibre such as jute and coir fibre, sisal fibre, rice husk, bagasse fibre can be used effectively along with cementitious material in the construction of various components of a building [2]. Compressed stabilized earth blocks are manufactured by compressing the soil, in a mechanical or hand press, into the desired form along with stabilizers. With these blocks, shells are constructed which are in pure compression form eliminating the need for any tension component or reinforcements from a structure. As this is unreinforced masonry structure it will not perform well in seismic loading. Cracks are likely to develop and this will create problems regarding waterproofing. It will cause frequent repair and maintenance to such structures [4]. Prefabricated bamboo reinforced walls can be used as a component for low cost housing as they are 56% lighter in weight and 40% cheaper and having good strength as compared to brick masonry walls [6]. Industrial and agro waste such as cotton mill waste, recycled paper mill waste and rice husk ash shall also be included in productions of bricks which can then be used in low cost housing construction [5]. Lack of awareness, lack of manufacturers, and no proper supply chain management are the problems on which efforts are necessary so that effective use of materials can be achieved in low cost housing.

3. APPLICABILITY OF COMPOSITE CONCRETE BLOCKS IN LOW COST HOUSING Low Cost Housing projects are mostly located in rural areas or hilly regions with little or no connectivity in terms of roads and other transport means. It will be very difficult to transport the construction material and equipment like formwork, concrete mixer etc. to such sites and then carrying out all the procedure of batching, mixing, placing etc. This will increase in overall cost including transportation cost, will cause delays and economy of the project will get affected. Casting of composite concrete blocks in a well-controlled environment in a casting yard by carrying out all the stepwise procedure will serve a solution for this. Transporting these blocks to such project sites will be more convenient and erecting Low Cost Housing units with little time become possible. Construction of walls of Low Cost Housing units by using composite concrete blocks is very easy and does not involve complicated fittings. Any semi-skilled labour having knowledge of conventional brick masonry can do this job. This will eliminate the need of labours with special skills and reduce the labour cost.

4. DEVELOPMENT OF COMPOSITE CONCRETE BLOCKS Following are the details of materials to be used

4.1 Materials 4.1.1 Cement Ordinary Portland Cement of 53 Grade (OPC 53) having the designed compressive strength of 28 days as 53 MPa or 530 kg/cm2.

4.1.2 Natural Fiber (Coir) Coir fiber is the type of natural fiber which is extracted from fibrous outer cover of coconut. Coir fiber is very light weight and brown in color. It has threads of typically 10 to 30 centimeters (4 to 12 in) long and 10 to 20 μm (0.0004 to 0.0008 in) in diameter. [135] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 4.1.3 Sugarcane Bagasse Ash Ash which is obtained by controlled burning of sugarcane bagasse is called sugarcane bagasse ash. Such ash to be sieved through 300 μm standard IS sieve and sample passing through sieve shall be taken for experimental study.

Fig. 1: Sugarcane Bagasse Ash

4.1.4 Water Potable water accessible within laboratory to be used for mixing and curing of samples.

4.1.5 Aggregate The aggregates used in the manufacture of blocks at the mixer or the mixing platform shall be clean and free from deleterious matter. Natural aggregate in which fine aggregate passing through standard IS sieve 4.75 mm and coarse aggregate passing through IS sieve 20 mm and retaining on IS sieve 4.75 mm are to be taken for sample preparation.

4.2 Proportioning and Sample Preparation Samples of a composite were prepared by using the above stated materials in a proportion of 1 (cement + sugarcane bagasse ash): 1.5 (fine aggregate): 3 (coarse aggregate). Sugarcane bagasse ash was added as 0% to 30% replacement of total quantity of cement to be used. Natural coir fibre was added by 3 % to 4 % of the total volume of the sample and w/c ratio of 0.45 was adopted. Proportions in which 0%, 10%, 20%, 30% cement is replaced with sugarcane bagasse ash are termed ash CCB0, CCB10, CCB20, CCB 30, where CCB stands for Composite Concrete Blocks.

Fig. 2: Composite Concrete Block using Bagasse Ash

4.3 Laboratory Tests Following are the details of laboratory tests carried out to determine properties of composite concrete blocks such as compressive strength and block density. [136] Laboratory Analysis of Bagasse Ash and Coir Fiber Composite Concrete Blocks for Low Cost Housing 4.3.1 Compression Test A series of compression tests were carried out to determine compressive strength by using Compression Testing Machine (CTM). Block specimen of surface area 4 inch x 8 inch and 80 mm height were prepared of selected proportions. Minimum 9 full size units of each were made of selected proportions for testing after 3 days, 7 days and 28 days each mixing under CTM. The strength of the full size units is considered as that which was calculated from the average measured strength of the segments. The age was reckoned from the time of the addition of water to the dry ingredients. The compressive strength of a concrete masonry unit was taken as the maximum load, in Newtons, divided by the gross cross-sectional area of the unit, in square millimetres. The gross area of a unit is the total area of a section perpendicular to the direction of the load.

4.3.2 Method for The Determination of Block Density Three blocks of each proportion were taken at random from the samples. Each was measured in centimeters (to the nearest millimeter) and the overall volume computed in cubic centimeters. The block was then weighed in kilograms (to the nearest 10 g) and the density of each block calculated as follows:

The average for the-three blocks was taken as the average density.

4.4 Results and Discussion Following are the test results which was obtained during detailed laboratory experimentation carried out to study of the varying effect on compression strength and block density of concrete blocks due to partial replacement of cement with sugarcane bagasse ash and incorporation of coir fibre. Mean compressive strengths (N/mm2) of all the proportions tested are summarized in the following table.

Table 1: Mean Compressive Strength Values of all CCB Proportions Blocks with Cement Replacement Mean Compressive Strength (N/mm2) 3 Days 7 Days 28 Days 0% 16.73 22.90 28.307 10% 13.16 18.34 22.94 20% 11.99 17.33 21.24 30% 10.83 15.82 19.71

Fig. 3: Graph Showing Mean Compressive Strengths of all CCB Proportions

[137] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Following are the details of average block densities calculated.

Table 2: Average Block Densities of all CCB Proportions Blocks with Cement Replacement Block Density 0% 1917.33 Kg/m3 10% 1894.33 Kg/m3 20% 1857 Kg/m3 30% 1826.67 Kg/m3 Blocks with all types of proportions tested in this project work satisfy the requirement of minimum average compressive strength of 5 N/mm2 and minimum block density of 1800kg/m3 in case of solid concrete blocks mentioned in IS 2185 (Part 1): 2005[1]. Walls to be constructed from above blocks will be load bearing walls and will eliminate the need of load bearing members such as RCC column or steel column in low cost housing models which are usually single slab structures. For this purpose, considering strength and safety as the first priority, the target compressive strength of blocks was kept at least 20 N/mm2. Considering the above test results obtained from Compression test of blocks, it is observed that the blocks which are having sugarcane bagasse ash as a replacement of 30% of the total quantity of cement are having average compressive strength 19.71 N/mm2 which is below the target strength of 20 N/mm2. While the blocks which are having sugarcane bagasse ash as a replacement of 0%, 10% and 20% of the total quantity of cement are having average compressive strength well above 20 N/mm2. The concrete blocks with sugarcane bagasse ash as 20% replacement of cement are having required compressive strength and will reduce the cost considerably.

5. CONCLUSION According to detailed laboratory analysis carried further, the blocks with the proportions CCB0, CCB10, CCB20, CCB30 have mean compressive strengths at 28th day after casting are 28.307 N/mm2, 22.94 N mm2, 21.24 N/ mm2, 19.71 N/mm2 respectively and block densities of all the proportions were above 1800 kg/m3. Considering both compressive strength and cost reduction in mind the concrete blocks with sugarcane bagasse ash as 20% replacement of cement will serve as an optimum solution. In this blocks quantity of cement required will be replaced by sugarcane bagasse ash by the amount of 20% so this will directly result in the saving of cost of cement which is the major factor in manufacturing cost. Use of locally available material such as coir fibre and industrial waste such as bagasse ash will serve eco-friendly solution and help in cost reduction in Low Cost Housing projects.

ACKNOWLEDGEMENTS This project work has been carried out in Civil and Environmental Engineering Department, Veermata Jijabai Technological Institute, Mumbai, India.

REFERENCES [1] IS 2185 (Part 1): 2005, Concrete Masonry Units — Specification Part 1 Hollow and Solid Concrete Blocks. [2] Manjesh Srivastava, Vikas Kumar (2018), “The methods of using low cost housing techniques in India”, Journal of Building Engineering, Elsevier, volume 15 (2018), pp. 102–108. [3] Report of the technical group on urban housing shortage (TG-12), Ministry of Housing and Urban Poverty Alleviation, 2012–2017. [4] Ryan A. Bradley and Mitchell Gohnert (2018), “Compressed Stabilized Earth Block Shell Housing: Performance Considerations”, Practice Periodical on Structural Design and Construction, ASCE, Volume 23 Issue 3 - August 2018, 04018009.

[138] Laboratory Analysis of Bagasse Ash and Coir Fiber Composite Concrete Blocks for Low Cost Housing

[5] Saurabh N. Joglekar, Rhushikesh A. Kharkar, Sachin A. Mandavgane, Bhaskar D. Kulkarni (2018), “Sustainability assessment of brick work for low-cost housing: A comparison between waste based bricks and burnt clay bricks”, Sustainable Cities and Society, Elsevier, volume 37 (2018), pp. 396–406. [6] Vishal Puri, Pradipta Chakrabortty, Sourav Anand, Swapan Majumdar (2017), “Bamboo reinforced prefabricated wall panels for low cost housing”, Journal of Building Engineering, Elsevier, volume 9 (2017), pp. 52–59. [7] Vishal Puri, Pradipta Chakrabortty, Swapan Majumdar(2015), “A Review of Low Cost Housing Technologies in India ”, Advances in Structural Engineering, Springer, volume 3(2015), pp. 1943–1955.

[139] Laboratory Investigation of Charcoal Coconut Shell Ash Modified Bitumen

Abhishek Dnyaneshwar Mahajan1 and Dr. Sumedh Mhaske2 1M.Tech. (Const. Management) Scholar, Department of Civil & Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Associate Professor and HOD, Department of Civil & Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected], [email protected]

ABSTRACT This study was conducted to investigate the suitability of use charcoal coconut shell ash as a bitumen modifier. Bitumen properties which relates to high endurance to temperature and traffic are the primary requisites in enhancing the pavement life. Rutting and fatigue failures are problems in pavement engineering that heads to innumerable studies for enhancing pavement performance. Bitumen alteration by charcoal coconut shell ash material is a process that has the potential to change the working of asphalt mixtures due to the available large surface area and small size. This investigation focused on micro sized (less than 100µm) charcoal from coconut shell as an additive in bitumen. Micro sized charcoal ash (MCA) produced by abrasion test and blast furnace is used. After that 0% (conventional), 1%, 2%, 3%, 4%, 5% and 6% by weight of binder PEN 60/70 ash was added. Ductility, softening point, penetration and viscosity tests were accomplished to scrutinize the physical properties of modified bitumen. Results disclosed that MCA decreased the ductility and penetration whereas increased the viscosity and softening point of the bitumen. The results concluded that 5% optimum addition of charcoal is possible to reduce the binder content in the mix. Keywords: Charcoal Coconut Shell Ash, Conventional Bitumen, Modified Bitumen

1. INTRODUCTION

1.1 General Road transportation is vital to India’s developing economy. Road network carries 65% of its freight traffic and 85% of its passenger’s traffic. So providing the best road pavement becomes important priority. Bitumen is well known as good adhesives and load resistant materials appropriate for paving applications. As they are viscoelastic materials, they experience several modes of failure under different temperature conditions throughout their service life. Many facts and verification studies proved that the bitumen we use today need advancement and superior endurance as rutting and fatigue becomes very serious problems for bitumen failures. Fundamental dynamic that lead to pavement distress is the deprived bitumen properties. Various nanomaterials are in practice to heighten the physical and rheological properties of bitumen. Use of charcoal coconut shell ash is an interesting alternative from both economic and environmental perspectives. Small scale powder materials exhibit higher reactivity compared with other common-sized particles because of their small size. An appropriate stiffness and fluidity of binder is favorable to attain at the same time for rutting resistance and workability of bitumen at service temperatures. There are several test at disposal to check the various parameters of bitumen to see its acceptable range in numerous applications of pavement, roofing etc. There are earlier examination on nanomaterials to mutate the properties of bitumen but most of them have utilized the inorganic materials so one of the way to address this issue is to replace these materials with

[140] Laboratory Investigation of Charcoal Coconut Shell Ash Modified Bitumen organic alternatives such as charcoal coconut ash. In addition, the charcoal coconut ash is environmentally friendly due to its biodegradability and discharge of a rather lesser amount of carbon dioxide when burned. Therefore, this study aimed on the utilization of charcoal ash from coconut shell as the modifier and its consequences on bitumen functioning. Ductility, softening point, penetration and viscosity tests were performed to examine the conclusions of powder sized charcoal on the physical properties of bitumen.

1.2 Objectives of Study Identify different substitute materials to improve the physical properties of the bitumen and select it. Utilizing the suitable charcoal coconut ash in various bitumen tests for comparing the original bitumen with modified bitumen according to the result.

2. LITERATURE REVIEW

2.1 General: Bitumen as Construction Material The asphalt pavement is a type of road infrastructure that enables vehicles to travel from one place to structures [9]. This strong and durable infrastructure presents a smooth surface to provide safe riding quality for road users [9]. The most dire pavement distresses in flexible pavements are permanent deformation at high temperatures, fatigue cracking at intermediate temperatures, and thermal cracking at low temperatures [2]. Various types of nanomaterials have been used to modify the binder. Among all waste materials, coconut shell seems to have the potential to be fashioned as nanomaterial because of its strength and good quality in various composite structures. Though there are considerable numbers of conference and seminars, but still in India mostly the roads are with flexible pavements. A lot of study on use of Waste materials has been made but the part of this material is still somewhat restricted. So by taking holistic approach identify the region where this material seems fit. Performance of standard bitumen may not be considered satisfactory because of the following reasons:

Table 1: Flexible Pavement Defects Due to Poor Bitumen Performance Region / Climate Reason Defects Summer season / Hot regions Excessive temperature Bleeding, rutting and segregation Winter season Low temperature Cracking, raveling and unevenness Rainy season Water penetrates Pot holes and layer removal Hilly areas / Cold regions Sub-zero temperature, freeze thaw and Volume expansion and contraction in heave cycle voids The price of bitumen has been escalating constantly. In upcoming time, there will be deficiency in supply of bitumen and it will be unfeasible to procure bitumen at very high costs. Continuing rapid industrialization and strong growth in building construction markets are driving demand for bitumen in the paving market, especially with the country undergoing the most dramatic growth in road building of nation, which will spur demand for bitumen used in paving grade bitumen, modified bitumen, bitumen emulsions and other paving applications (interface treatments).

2.2 Charcoal Coconut Shell Ash: An Inventive Solution To modify the pavement performance in rutting, cracking and extending longevity of the roadways, innovative modified binders have been broadly utilize in flexible pavement. Various types of nanomaterials, such as Nano clay, Nano silica, carbon nanofiber (CNF), and others, have been used to modify the binder[8]. This material exhibits several benefits and prospects for modifying the behaviour of base bitumen,

[141] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) especially for flexible pavement applications. Previous studies on nanomaterials mostly utilized inorganic nanomaterials in the bitumen [8]. One of the approaches to mitigate the risks of using hazardous materials on the environment, health, and safety is to interchange these materials with an alternatives [8]. Given the environmental, health and safety concerns, the use of natural sources, such as nanomaterials from waste materials, can help to mitigate the risks of hazardous nanomaterials and are environmental friendly. Coconut is an extremely strong, rigid, and lightweight material [8]. Many of the research has been done in concrete technology with coconut shell as trade aggregate. Coconut shell is broadly used for making charcoal. Further this charcoal is use as basic ingredient for activated carbon production. Sri Lanka, India and other Pacific countries where the coconut trees are available in huge numbers. Despite the relatively large number of papers devoted to the study of processing variables on bituminous materials, there is rarely any research for bitumen by adding coconut waste in prolonging the pavement life.

Fig. 1: Charcoal Coconut Shell Ash

3. METHODS Detailed methodology and materials are described in this chapter for better understanding of the practical and laboratory testing of the materials.

3.1 Methodology ●● Studying various bitumen pavement defects and finding appropriate solution to it respectively. ●● Exploring several natural as well as artificial bitumen substitute materials as modifiers to address the defects of bitumen by changing its properties ●● Analysing the materials as unique option to diminish the bitumen defects to prolong the core strength of bitumen. ●● Identification of coconut shell as basic material for charcoal ash powder through previous findings, literature, research papers etc. ●● Prepare the charcoal ash powder with help of furnace and Los Angeles abrasion test and procure the ash powder which will pass through 75 µm sieve ●● Mix the ash powder in bitumen and perform all the essential bitumen tests such as penetration test, softening point test, viscosity test, ductility test to check the effects of changes in different properties bitumen. ●● Complete the investigation on the basis of results acquired through the tests.

3.2 Materials Following materials are used for laboratory testing purpose.

[142] Laboratory Investigation of Charcoal Coconut Shell Ash Modified Bitumen 3.2.1 Binder The bitumen PEN 60/70 grade is used.

Table 2: Bitumen Properties

Property Value

Ductility test (cm) 108

Softening point (°C) 47.5

Penetration at 25°C (dmm) 66

Viscosity at 135°C (Pa/s) 0.34

Specific gravity 1.0175

3.2.2 Charcoal Ash Coconut shell was burnt in a furnace at 450°C for 5 min. This temperature was selected based on the thermal properties of charcoal. Then powder has been produced with help of manual rod tamping. Adding the coconut shell ash with help of asphalt mixer in the hot bitumen to produce the modified bitumen.

3.3 Bitumen Tests There are several tests included to present the various characteristics and properties of bitumen as follows: ●● Ductility Test: The ductility is property of bitumen that enables it to undertake great deformation or elongation. The ductility is referred as the distance in cm, to which a standard model sample or briquette of the material will be elongated deprived of breaking. The bitumen sample is heated and poured in the mould assembly positioned on a plate. The distance up to the stage of cracking of thread is the ductility value which is measured in cm. ●● Softening Point Test: Softening point signifies the temperature at which the bitumen reach a specific degree of softening under the condition of test. The test undergoes with help of Ring and Ball apparatus. Temperature is duly noted when the softened bitumen contacts the metal plate which is at a specified particular distance below them. Usually, higher softening point suggests lower temperature susceptibility and is preferred in hot regions. ●● Penetration Test: Penetration value on bitumen is a degree of hardness or consistency of bituminous material. An 80/100 grade bitumen signifies that its penetration value is in between 80 & 100. Penetration value is the vertical distance travelled or penetrated by the point of a traditional needle into the bituminous material under particular conditions of load, time and temperature. This distance is quantified in one tenths of a millimeter. ●● Viscosity Test: It is used to determine viscosity of liquid bitumen. In this test, we use Brookfield Viscometer which a rotational viscosity provider to determine the specific value of bitumen.

[143] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 2: Ductility Test Fig. 3: Softening Point Test

4. RESULTS Following Table gives the comparative study of change in the properties of the original bitumen and modified bitumen. We will observe the change with respective to the change in the charcoal content by percentage of the weight in bitumen.

Table 3: Test Results

Ductility Test Softening Point Test Penetration Test Viscosity Test Tests (cm) (°C) (mm) (Pa/s) Conventional Bitumen (0% addition of charcoal coconut 108 47.5 66 0.34 shell ash by weight) - CB Modified Bitumen (1% addition of charcoal coconut 95 52 56 0.55 shell ash by weight) – MB1 Modified Bitumen (2% 88 53 55 0.58 addition) – MB2 Modified Bitumen (3% 84 54 50 0.61 addition) – MB3 Modified Bitumen (4% 78.5 54.5 49 0.62 addition) – MB4 Modified Bitumen (5% 75.5 54.5 45 0.73 addition) – MB5 Modified Bitumen (6% 59 56 42 0.81 addition) – MB6 Recommended Values by MCGM Technical Road 75 min 45–55 range 35 min 0.15 min Specifications Vol. II

[144] Laboratory Investigation of Charcoal Coconut Shell Ash Modified Bitumen

Fig. 4: Test Results of Conventional and Modified Bitumen

Viscosity test (Pa/s) 1

0.8

0.6

0.4

0.2

0 CB MB1 MB2 MB3 MB4 MB5 MB6

Fig. 5: Viscosity Test Results of Conventional and Modified Bitumen

5. CONCLUSIONS ●● The bitumen modified by charcoal coconut shell ash showed changes in physical properties. ●● The large surface area of charcoal coconut shell ash form strong particle interaction with the bitumen. Thus, the cohesion of the bitumen increased, consequently increasing the stiffness. Penetration value of the modified bitumen showed promising results. ●● Most of the results found in the tests approved the replacement of bitumen with microcharcoal ash except the ductility test of MB6 which is lesser than recommended value after the mixing. ●● From all the above test results of physical properties of bitumen 5% reduction is possible for the paving application in hot regions. ●● From the previous studies and current findings it can be conclude that finer the particle size of charcoal ash ensure the higher substitution in bitumen.

[145] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) REFERENCES [1] Ahmed Abdulameer Hussein, Ramadhansyah Putra Jaya, Norhidayah Abdul Hassan, Haryati Yaacob, Ghasan Fahim Huseien, Mohd Haziman Wan Ibrahim (2017). “Performance of nanoceramic powder on the chemical and physical properties of bitumen”, Construction and Building Materials, Elsevier, volume 156, pp. 496-505. [2] Conglin Chen, Joseph H. Podolsky, R. Christopher Williams, Eric W. Cochran (2018). “Laboratory investigation of using acrylated epoxidized soybean oil (AESO) for asphalt modification”, Construction and Building Materials, Elsevier, volume 187, pp. 267-279. [3] G.H. Shafabakhsh, O. Jafari Ani (2015) “Experimental investigation of effect of Nano TiO2/SiO2 modified bitumen on the rutting and fatigue performance of asphalt mixtures containing steel slag aggregates”, Construction and Building Materials, Elsevier, volume 98, pp. 692-702. [4] Gatot Rusbintardjo, Mohammad Rosli Hainin, Nur Izzi Mohammad Yusoff (2013) “Fundamental and rheological properties of oil palm fruit ash modified bitumen”, Construction and Building Materials, Elsevier, volume 49, pp. 702-711. [5] IS 1201 – 1220 (1978), Methods for testing tar and bituminous materials. [6] K. Gunasekaran, P.S. Kumar, M. Lakshmipathy (2011). “Mechanical and bond properties of coconut shell concrete”, Construction and Building Materials, Elsevier, volume 25, pp. 92-98. [7] Technical Specification for Road Works 2013, Volume II, Road Department, Municipal Corporation of Greater Mumbai. [8] Siti Nur Amiera Jeffry, Ramadhansyah Putra Jaya, Norhidayah Abdul Hassan, Haryati Yaacob, Jahangir Mirza, Siti Hasyyati Drahman (2018). “Effects of nanocharcoal coconut-shell ash on the physical and rheological properties of bitumen”, Construction and Building Materials, Elsevier, volume 158, pp. 1-10. [9] Siti Nur Amiera Jeffry, Ramadhansyah Putra Jaya, Norhidayah Abdul Hassan, Haryati Yaacob, Mohd Khairul Idham Mohd Satar (2018). “Mechanical performance of asphalt mixture containing nanocharcoal coconut shell ash”, Construction and Building Materials, Elsevier, volume 173, pp. 40-48.

[146] Determination of Mixing and Compaction Temperatures of Asphalt Binders Modified with EPDM Rubber Waste

Ankush Kumar1, Rajan Choudhary2 and Abhinay Kumar3 1M.Tech. Student, Department of Civil Engineering, Indian Institute of Technology Guwahati, Assam, India 2Professor, Department of Civil Engineering, Indian Institute of Technology Guwahati, Assam, India 3Research Scholar, Department of Civil Engineering, Indian Institute of Technology Guwahati, Assam, India E-mail: [email protected], [email protected],3 [email protected]

ABSTRACT Mixing and compaction temperatures of an asphalt binder play a vital role in the production and placement of asphalt mixes. Appropriate mixing and compaction temperature helps to achieve proper coating of asphalt binder over aggregates during mixing and an adequate density of the mix during compaction. Equiviscous method specified in Asphalt Institute’s Manual Series-2 is the most commonly employed method to determine the mixing and compaction temperatures of neat/unmodified asphalt binders. However, this method may not be able to produce reliable results in the case of modified asphalt binders. In this study, four different methods, namely the equiviscous method, high shear viscosity method, zero shear viscosity method, and phase angle method, have been used to determine the mixing and compaction temperatures of neat asphalt binder and asphalt binders modified using ethylene-propylene- diene-monomer (EPDM) rubber waste. EPDM, a synthetic rubber, is a terpolymer of ethylene, propylene and a diene monomer and is widely used in non-tyre automotive rubber products. EPDM rubber wastes are mainly generated from rubber industries, manufacturing units and automobile repair/service stations. Modified asphalt binders were prepared with four EPDM contents (0, 2, 4 and 6% by weight of the binder). The phase angle method produced lower mixing and compaction temperatures compared to the equiviscous and high shear viscosity methods, and was finally recommended for use with EPDM modified asphalt binders. Keywords: Production Temperatures, EPDM Rubber Waste, Phase Angle, Zero Shear Viscosity, High Shear Viscosity

1. INTRODUCTION Globally, the highway agencies have recognised the benefits of using modified asphalt binders (or modified bitumen) to tackle growing heavy axle loads, climatic variations, the consequent severity of pavement distresses, and to prolong the service life of the bituminous pavements (Kandhal, 2006; Kumar et al., 2018). For a tropical country like India where air temperatures can reach 50–55°C, one main aim to employ suitable additives/modifiers with the neat binders is to get modified binders having enhanced rutting resistance (resistance to the accumulated permanent deformation). A variety of synthetic polymers are widely used for modification of neat asphalt binders, so as to improve their engineering properties in terms of the resistance to permanent deformation (rutting), fatigue, moisture damage and oxidative aging. Use of waste polymer and waste rubber in asphalt binder modification is an encouraging step forward to sustainability in the asphalt industry since these materials pose disposal issues and do not self- decay with time. Ground rubber (or crumb rubber) from waste automobile tyres is one of the waste rubbers being widely utilised to improve the pavement performance (Kandhal, 2006; Tang et al., 2016; Zhang and Hu, 2015; Julaganti et al., 2019). However, the evaluation of asphalt binder modification with ethylene- propylene-diene monomer (EPDM), a widely used rubber in non-tyre automobile components, is still not well-explored. EPDM, a terpolymer of ethylene, propylene and a diene monomer, is a high quality rubber and finds a broad range of applications in non-tyre automotive parts such as tyre flaps, gaskets, weather strips, belts and window seals (Barlow, 1988). EPDM rubber wastes are generated from several industries, manufacturing units and automobile repair/service stations. [147] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Mixing and compaction temperatures (collectively referred to as production temperatures) play a significant role in achieving the desired mix volumetric properties and workability. At the mixing temperature, binder viscosity should be low enough to allow complete coating of aggregates during mix preparation. At the compaction temperature, binder viscosity should be sufficient to provide workability allowing the movement of aggregates in a dense configuration to achieve the desired in-situ density and air voids. Too low mixing temperature can lead to poor binder coating and thus render the mix susceptible to moisture-induced damages. Too low compaction temperature can lead to insufficient mix compaction or a difficult compaction (Mo et al., 2012). Insufficient compaction is regarded as the primary cause of major pavement distresses such as rutting, ravelling, cracking and moisture damage. The equiviscous method stipulated by the Asphalt Institute has been in use since 1962 for determination of production temperatures of neat asphalt binders. The mixing temperature is defined as the temperature required to produce a viscosity of 0.17 ± 0.02 Pa.s, whereas compaction temperature is the temperature at which binder attains a viscosity of 0.28 ± 0.03 Pa.s (Asphalt Institute, 2015). This method helps to normalise the effect of binder stiffness on volumetric properties of the mixtures. However, the use of modified asphalt binders requires the selection of appropriate production temperatures. The equiviscous method may not hold good for modified asphalt binders. When applied to modified binders, the method often results in unreasonably high mixing and compaction temperatures (sometimes exceeding 180 °C). Excessively high production temperatures may pose safety risks and result in degradation to the modifier, damage to the binder with changes in its chemistry, excessive energy and fuel consumption in the plant, and generation of fumes during mix production (Yildirim et al., 2000; Shenoy, 2001; Asphalt Institute, 2015).

2. RESEARCH OBJECTIVES The main objective of this study is to compare different approaches commonly used to determine mixing and compaction temperatures, for asphalt binders modified with EPDM rubber waste. The four approaches considered in the study for finding the mixing and compaction temperatures include: (1) the equiviscous method; (2) high shear viscosity (HSV) method; (3) zero shear viscosity (ZSV) method; and (4) phase angle method. Each of the methods is discussed and the production temperatures determined are compared with those of the control binder (unmodified binder) through the equiviscous method.

3. MATERIALS A widely used viscosity graded (VG-30) binder in India was selected as the control binder in this study. Properties of the control binder are given in Table 1. EPDM rubber waste used in the study was obtained from non-tyre automotive parts and further shredded into granules that passed the 300-micron sieve. Four EPDM contents (0, 2, 4, and 6% by weight of neat binder) were used to prepare the modified asphalt binder blends. Blending was done using a high shear mixing rate of 8000 rpm for 45 min at a temperature of 170 °C. Figure 1a shows the EPDM rubber granules used in the study and Figure 1b shows the blending operation.

Table 1: Properties of Base Binder (VG-30) Property Requirementsa Results Penetration at 25°C, 100 g, 5 s, 0.1 mm min 45 50.0 Absolute viscosity at 60°C, poise 2400–3600 2880 Kinematic viscosity at 135°C, cSt min 350 510 Flash point (COC), °C min 220 280 Solubility in trichloroethylene, % min 99 >99 Softening point (R&B), °C min 47 54.3 Tests on rolling thin film oven (RTFO) Residue Viscosity ratio at 60°C max 4 2.85 Ductility at 25°C, cm min 40 64 aRequirements as per IS: 73 (2013), Indian Standard on ‘Paving Bitumen Specification’. [148] Determination of Mixing and Compaction Temperatures of Asphalt Binders Modified with EPDM Rubber Waste

(a) (b) Fig. 1: (a) EPDM Rubber Granules, (b) Blending Operation using a High Shear Mixer

4. METHODS FOR DETERMINATION OF MIXING AND COMPACTION TEMPERATURES Various methods are used globally by researchers to determine the mixing and compaction temperatures of asphalt binders (neat and modified). The critical factors that are to be considered are that the mixing temperature should be high enough to ensure adequate fluidity to have uniform binder coating on the aggregates and the final discharge should not cool below the compaction temperature. The compaction temperature should be selected such that the aggregates can reorient into a dense mass at a specified compaction effort. The mixing and compaction temperatures should also take care of the excessive aging and degradation aspects of the asphalt binder (Shenoy, 2001). The four main approaches to determine the mixing and compaction temperatures are discussed next along with the results obtained. All tests were performed on unaged binders.

4.1 Equiviscous Method The equiviscous method is the most widely used method for the determination of mixing and compaction temperature ranges for bituminous mixes with neat asphalt/bituminous binders. As specified in Asphalt Institute’s Manual Series-2, the main idea behind using the equiviscous method is to normalise the effect of asphalt binder stiffness on mixture volumetric properties. In the equiviscous method, the viscosity of the asphalt binder is determined at two test temperatures (typically 135 and 165 °C) and one shear rate (typically, 6.8 1/s corresponding to 20 rpm) using the spindle #21 in a rotational viscometer. The determined viscosity is plotted on log-log scale vs log temperature (°R). Mixing and compaction temperatures are determined where the viscosity- temperature line crosses the viscosity range of 0.17 ± 0.02 Pa.s and 0.28 ± 0.03 Pa.s, respectively. Figure 2 shows the determination of the mixing and compaction temperature range for the control binder. A similar procedure has been followed for EPDM modified binders.

Fig. 2: Viscosity-temperature Profile for Equiviscous Method for Control Binder [149] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) The main disadvantage of this method is that it assumes that all asphalt binders are Newtonian in nature whose viscosity is independent of shear rate. However, the modified asphalt binders exhibit pseudoplastic behaviour, often referred to as shear thinning where viscosity values depend on shear rate (Yildirim et al., 2000). Thus, this method does not yield reliable results for the modified asphalt binders.

4.2 High Shear Viscosity Method Yildirim et al. (2000) developed this method which relies on the idea that most of the modified binders show shear thinning behaviour. In this method, viscosities of the asphalt binder over a range of shear rates is measured at two test temperatures (typically 135 and 165 °C) using a rotational viscometer. The data is then extrapolated to a higher shear rate of 500 1/s and plotted on a log-log viscosity vs log temperature (°R) chart to obtain temperatures that correspond to the traditional viscosity criteria of 0.17 ± 0.02 Pa.s for mixing and 0.28 ± 0.03 Pa.s for compaction. In this study, extrapolation of the data has been performed using two models, namely the Power law model and the Cross-Williams model.

4.2.1 Power Law Model Equation for the Power Law model is presented as Eq. 1. η = K n (1)

Here,γ ղ is−1 the viscosity, γ is the shear rate, K and n are the model coefficients. 4.2.2 Cross-Williams Model Equation for the Cross-Williams model is presented as Eq. 2. η = η + (ηο −η∞ ) (2) ∞ 1+ (Kγ )n

Here, ղ∞ is the limiting viscosity in the second Newtonian region, ղ0 is the zero shear viscosity, γ is the shear rate, K and n are the model coefficients. Figure 3 shows the model fit for Power law and Cross-Williams model at 135 and 165 °C. The model fitting is done using Origin v8.5 Pro software for the data set of viscosity and shear rate obtained using rotational viscometer, and the model parameters K and n for both the models are determined. These obtained model parameters are used to calculate the viscosity at a high shear rate of 500 1/s at both test temperatures (135 and 165 °C). Further, a linear relationship is established between the obtained viscosity and temperatures. Mixing and compaction temperatures are determined where the viscosity- temperature line crosses the viscosity range of 0.17 ± 0.02 Pa.s and 0.28 ± 0.03 Pa.s, respectively. Determination of mixing and compaction temperature range is shown in Figure 4a for Power law model and Figure 4b for Cross-Williams model. A similar procedure has been followed for other binders used in this study.

(a) (b) Fig. 3: Model Fit for Control Binder using (a) Power Law Model, (b) Cross-Williams Model [150] Determination of Mixing and Compaction Temperatures of Asphalt Binders Modified with EPDM Rubber Waste

4.3 Zero Shear Viscosity Method In this method, Cross-Williams model is again used to fit a curve for the data set of viscosity and shear rate obtained using rotational viscometer. The model fitting is done using Origin v8.5 Pro software and the model parameters K and n are determined. These obtained model parameters are again used to estimate the viscosity at a shear rate of 0.001 1/s at both test temperatures (135 and 165 °C). The obtained shear viscosities at both the test temperatures are then used to establish a relationship between viscosity in Pa.s and temperature in degree Rankine scale. Figure 5 shows the plot for the control binder. The mixing and compaction temperatures are determined where the viscosity-temperature line crosses the viscosity range of 3.0 ± 0.3 Pa.s and 6.0 ± 0.6 Pa.s, respectively (Bahia et al., 2001). A similar procedure has been followed for other binders used in this study.

(a) (b) Fig. 4: Viscosity-temperature Profile for Control Binder in High Shear Viscosity Method using (a) Power Law Model, (b) Cross-Williams Model

Fig. 5: Viscosity-temperature Profile for Control Binder in Zero Shear Viscosity Method

4.4 Phase Angle Method This method has been suggested in NCHRP Report 648 (West et al., 2010), which is based on the concept that the phase angle is a measure of binder consistency that accounts for the viscoelastic nature

[151] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) of asphalt binder. In this method, a frequency sweep is performed on unaged asphalt binder using 25 mm plate and 1 mm gap in a dynamic shear rheometer (DSR). The frequency sweeps are performed at four temperatures (typically 50, 60, 70 and 80 °C) and at varying frequencies from 0.1 to 100 rad/s. The strain

is kept constant at 12%. Phase angle master curves are then developed from the obtained data using a reference temperature of 80 °C. Figure  6 shows the phase angle and complex modulus master curves log Glog *  G *     For complexFor complex modulus:for the modulus: control binder. Both the complex(   log modulus)   and phase angle master curves(3) are(3) developed using a (1  e(1  e(r ) log r) )

sigmoidal model given in Eq. 3 and 4.   For complex modulus:log log      For complex modulus: G  *    G *     (3) For phaseForFor phase angle: complex angle: modulus: (  (log  (r log )  logr) r )   (4) (4)(3) (3) (1 (1 e(1 e e(1) e) ( ) log r) )

Here,Here, ν is theν is lower the lower asymptote, asymptote, α is theα is difference the  difference  between between the values the values of the of upper the upper and lowerand lower For phase angle:      (4) Forasymptotes, phaseasymptotes,For angle: phase β and angle:β γand are γ the are parametersthe parameters defining(  logdefiningr ) the shapthe eshap betweene between the asymptotesthe asymptotes(4) and theand(4) the (1  e (1  e) (  logr ) ) locationlocation of the of inflection the inflection point. point.

Here, ν Here,is the Here, νlower is the ν isasymptote, lower the lower asymptote, asymptote,α is the αdifference is α theis the difference difference between between betweenthe values thethe ofvalues the upperofof the the upperand upper lower and and lower lower asymptotes, asymptotes,asymptotes, ββ andand γβ are areand the the γ parameters areparameters the parameters defining defining the defining theshape shap between thee betweenshap thee betweenasymptotes the asymptotes the and asymptotes the and location the and of the inflection locationlocation of thepoint. inflection of the inflection point. point.

FigureFigure 6. Complex 6. Complex modulus modulus and phase and phaseangle masterangle master curves curves for control for control binder binder (Reference (Reference temperature: temperature: 80 °C) 80 °C)

The complexThe complex modulusFig. 6:modulus Complex master master Modulus curve curve is and shown Phaseis shown to Angle verify to Master verify the Curvesshifting the shifting for of Control the of data theBinder todata construct(Reference to construct theTemperature: the 80 °C)

phasephase angle angle master master curve. curve. A good A gooddata shiftdata shiftis verified is verified by a bysmooth a smooth complex complex modulus modulus master master Figure 6.Figure ComplexThe 6. complex Complexmodulus andmodulusmodulus phase and anglemaster phase master curve angle curves masteris shown fo rcurves control to verifyfo binderr control the (Reference shiftingbinder (Reference oftemperature: the data temperature: to80 construct°C) 80 °C) the phase angle curve.curve. As per As masterNCHRP per NCHRP curve. Report A Report good 648, datathe648, frequencyshift the frequencyis verified (ω) corresponding by(ω a) correspondingsmooth complex to δ =to 86° modulusδ = is 86° selected masteris selected as curve. the as Asthe per NCHRP Thereference complexreferenceThe point complex Reportmodulus pointfor this 648, formodulus mastermethod. this the method.frequency curvemaster The phaseisThe curve (shownω )phase correspondingangle is toshown angle ofverify 86° ofto is the 86°toverify considered shifting is= considered86°the is shiftingof selectedas the th e as data transitionof asth e the the totransition constructdatareference point to constructpointfrom pointthe from for thethis method. phasepurelypurely angle phaseviscous masterviscous Theangle behaviour phase curve.master behaviour angle A curve.to goodof viscoelastic86° to A data is viscoelasticgood considered shift data be ishaviour. shiftverified asbe thehaviour. is transition verifiedTheby a Thefrequencysmooth bypoint frequencya smoothfromcomplex corresponding purely complexcorresponding modulus viscous modulus tomasterbehaviour this to masterthis to viscoelastic curve.transitiontransition Ascurve. perphase behaviour. NCHRPAs phase angle per NCHRPangle Reporthas The been has frequency 648,Report beenreported the reported648, frequencycorresponding to the correl frequencyto (correlateω) correspondingwelltoate this(ω wellwithδ) transitioncorresponding withthe temperatureto the phaseδ =temperature 86° to angle δis =where selected 86°has where isbeenadequate selected as adequatereportedthe as the to correlate referenceaggregateaggregatereference point coatingwell forcoating point with andthis the formethod.lubricationand temperaturethis lubrication method. The duri phase ngwhere Theduri compactionangle ngphase adequate compaction of angle 86° can aggregateis of considered be86°can achieved isbe coating considered achieved as (West thande transition (Westaslubrication et th al.e transitionet, 2010). point al. during, 2010). from The point compaction The from can be purelyobtainedobtained purelyviscous frequencyachieved frequency viscous behaviour is used (West behaviouris usedinto et Eq. viscoelastical., in 5 Eq.2010). toand viscoelastic5 6 and toThe be determine6 haviour. obtainedto determine behaviour. thefrequencyThe mixing the frequency Themixing is( Tused mixfrequency ) ( T andcorrespondinginmix Eq.) compaction and 5corresponding compactionand 6 to to(T compdeterminethis ( )T tocomp this) the mixing transitiontemperatures.temperatures.transition phase(T mixangle phase) and has angle compaction been has reported been (Tcomp reported to )correl temperatures. toate correl wellate with well the with temperature the temperature where adequate where adequate aggregateaggregate coating coatingand lubrication and lubrication during compactionduring compaction can0.0135 be0.0135 achievedcan be achieved (West et (West al., 2010). et al., The2010). The For mixing temperature:For mixing temperature: Tmix (TFmix ) ( F325( )  325( )  ) (5) (5) obtainedForobtained frequencymixing frequencytemperature: is used inis usedEq. 5 in and Eq. 6 5to and determine 6 to determine the mixing the (mixingTmix) and (T mixcompaction) and compaction (Tcomp(5)) (Tcomp) temperatures.temperatures. 0.012 0.012 For compactionFor compactionFor temperature: compaction temperature: temperature: Tcomp (TcompF ) ( 300(F )  300() ) (6) (6) (6) 0.0135 0.0135 T    For mixingFor temperature:mixing temperature: mix ( F )T mix 325( (F ) ) 325( ) (5) (5) The obtainedThe obtainedThe temperatures obtained temperatures temperatures are then are thenconverted are converted then convertedfrom from °F to from °F °C. to°F Similar°C.to ° C. Similar Similar procedure procedure procedure has beenhashas beenbeen followed for followedfollowed for other for othermodified modified asphalt asphalt binde T binders with rs EPDMwith EPDM 0.012used usedin this0.012 in study. this study. For compactionFor compactionother temperature: modified temperature: asphalt binderscomp ( FwithT )comp 300(EPDM (F ) ) used 300( in )this study. (6) (6)

[152] The obtainedThe obtained temperatures temperatures are then are converted then converted from °F from to °C. °F Similarto °C. Similar procedure procedure has been has been followedfollowed for other for modified other modified asphalt bindeasphaltrs withbinde EPDMrs with usedEPDM in thisused study. in this study. Determination of Mixing and Compaction Temperatures of Asphalt Binders Modified with EPDM Rubber Waste 5. RESULTS AND DISCUSSION

5.1 Viscosity-shear Rate Profile Results of viscosity determined at 135 and 165 °C for EPDM modified asphalt binders using the rotational viscometer are shown in Figure 7. As can be seen, adding EPDM to the binder produces a significant increase in the viscosity at both test temperatures. The viscosity of the EPDM modified binders further increased with increase in EPDM dosages. Increase in viscosity at the higher test temperature 165 °C is lower compared to the increase at lower test temperature of 135 °C. For all binders, the viscosity at 135 °C remains well below the Superpave specified maximum limit of 3.0 Pa.s, which indicates the EPDM modified binders can produce adequate workability and pumpability during construction operations.

(a) (b) Fig. 7: Viscosity-shear Rate Profile (a) At 135 °C and (b) At 165 °C

5.2 Mixing and Compaction Temperatures Figure 8 shows the combined results of mixing and compaction temperatures obtained through various methods. Mixing and compaction temperature determined through all the methods show an increasing trend with the increase in EPDM content in the binder. All the binders had lower mixing and compaction temperatures as compared to the equiviscous method when determined through HSV method. However, within the HSV method, mixing and compaction temperature determined through the Power law model gave lower values as compared to the Cross-Williams model. HSV (Power law) method produced 5, 11, 10, and 1 °C lower mixing and 2, 9, 7, and 1 °C lower compaction temperatures for 0, 2, 4 and 6% EPDM content, respectively compared to the equiviscous method. HSV (Cross-Williams) method produced 4, 9, 2, and 0.5 °C lower mixing and 3, 5, 3, and 3 °C lower compaction temperatures for 0, 2, 4 and 6% EPDM content, respectively compared to the equiviscous method. ZSV method shows unrealistically low results. The low production temperatures with ZSV method indicate that the extrapolation to a very low shear rate does not seem to work well with the binders used in this study. The most likely reason for such behaviour is that at such low shear rates, the effect of the modifier is not completely mobilised. Furthermore, phase angle method yielded lower mixing and compaction temperatures than both the equiviscous and HSV methods. Compared to the equiviscous method, the phase angle method produced 4, 14, 20, and 27 °C lower mixing and 4, 13, 18, and 23 °C lower compaction temperatures for 0, 2, 4 and 6% EPDM content, respectively. However, the phase angle method is found to be the least sensitive to EPDM content.

[153] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

(a) (b) Fig. 8: (a) Mixing Temperatures, (b) Compaction Temperatures

6. CONCLUSIONS The present study investigated the mixing and compaction temperatures of asphalt binders modified with EPDM rubber waste. Four different approaches, namely the equiviscous method, high shear viscosity method, zero shear viscosity method, and phase angle method, were used to determine the mixing and compaction temperatures of control and EPDM modified binders. Based on the results and analyses, the following conclusions are drawn: ●● Mixing and compaction temperatures increased with increase in EPDM dosages when determined through all methods considered in this study. ●● Both the Power law and the Cross-Williams models used in HSV method produced lower mixing and compaction temperatures compared to the equiviscous method. ZSV method yielded unrealistically low mixing and compaction temperatures. ●● The phase angle method also produced lower mixing and compaction temperatures compared to the equiviscous and HSV methods. This method is found to be less sensitive to the EPDM content. One reason may be that only a small range of EPDM dosages (2% to 6%) were used in this study. The advantage with this method is that it is performed using a dynamic shear rheometer and takes into account the viscoelastic behaviour of the asphalt binders and is thus finally recommended for use with EPDM modified asphalt binders. ●● Performance evaluation of bituminous mixes with EPDM modified binders prepared at mixing and compaction temperatures determined through candidate methods of the study should be done further to fully understand the effect of production temperatures on mix volumetrics/ performance.

REFERENCES [1] Asphalt Institute Manual Series No. 2. (2015). Asphalt Mix Design Methods. Asphalt Institute, USA. [2] Bahia, H. U., Hanson, D. I., Zeng, M., Zhai, H., Khatri, M. A., & Anderson, R. M. (2001). NCHRP Report 459: Characterization of Modified Asphalt Binders in Superpave Mix Design. TRB, National Research Council, Washington, DC, 1-45. [3] Barlow F W. Rubber compounding: principles, materials, and techniques. M. Dekker, 1988. [4] Julaganti, A., Choudhary, R., & Kumar, A. (2019). Permanent Deformation Characteristics of Warm Asphalt Binders under Reduced Aging Conditions. KSCE Journal of Civil Engineering, 23(1), 160-172.

[154] Determination of Mixing and Compaction Temperatures of Asphalt Binders Modified with EPDM Rubber Waste

[5] Kandhal, P. S. (2006). Quality control requirements for using crumb rubber modified bitumen (CRMB) in bituminous mixtures. Journal of the Indian Roads Congress, 67, 99-104. [6] Kumar, A., Choudhary, R., Kandhal, P. S., Julaganti, A., Behera, O. P., Singh, A., & Kumar, R. (2018). Fatigue characterisation of modified asphalt binders containing warm mix asphalt additives. Road Materials and Pavement Design, 1-23. [7] Mo, L., Li, X., Fang, X., Huurman, M., & Wu, S. (2012). Laboratory investigation of compaction characteristics and performance of warm mix asphalt containing chemical additives. Construction and Building Materials, 37, 239-247. [8] Shenoy, A. (2001). Determination of the temperature for mixing aggregates with polymer-modified asphalts. International Journal of Pavement Engineering, 2(1), 33-47. [9] Tang, N., Huang, W., and Xiao, F. (2016). Chemical and rheological investigation of high-cured crumb rubber- modified asphalt. Construction and Building Materials, 123, 847-854. [10] West, R. C., Watson, D. E., Turner, P. A., & Casola, J. R. (2010). NCHRP Report 648: Mixing and Compaction Temperatures of Asphalt Binders in Hot-Mix Asphalt. Transportation Research Board of the National Academies, Washington, DC. [11] Yildirim, Y., Solaimanian, M., & Kennedy, T. W. (2000). Mixing and compaction temperatures for hot mix asphalt concrete (No. Report No. 1250-5). University of Texas at Austin. Center for Transportation Research. [12] Zhang, F., & Hu, C. (2015). The research for structural characteristics and modification mechanism of crumb rubber compound modified asphalts. Construction and Building Materials, 76, 330-342.

[155] Behaviour of Black Cotton Soil and Remedial Measures

Sunita Kumari1 and Amrendra Kumar2 1Associate Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Expansive soil generally exits in arid and semi-arid climate regions of the world which cause serious problems on civil engineering structures. Such soils swell when given an access to water and shrink when it dries out. Several attempts have been made to control the swelling and shrinkage behavior of these soils. The present study deals with the description of expansive soil and its shrink and swelling behavior. An experimental investigation is carried out to control these behaviour using different admixtures. It was observed that the free swelling index (%) of black cotton soil decrease when the admixtures are mixed with it. Initially, free swell index of black cotton soil (no admixtures mix) was 80%. After the mixing of 6% amount of lime, sand and cement in the black cotton soil, free swell index decreases respectively up to 55.5 %, 48%, and 40.5% respectively. It is also observed that with cement, the soil shows the least free swell index. Keywords: Free Swell Index, Black Cotton Soil, Lime, Cement and Sand

1. INTRODUCTION Engineering problems arises due to expansive soils have been reported in many countries all around the world. The millions of dollars used for repaired the severely damages structures. These damages are most common especially in the arid and semi-arid regions. Expansive soils contain the clay mineral montmorillonite with clay stones, shale’s, sedimentary and residual soils which are capable of absorbing great amount of water and expand. The expansive nature of the clay is high near the ground surface where the profile is subjected to seasonal and environment changes. Expansive soils also shrink when they dry out and fissures in the soil also developed. These fissures help water to penetrate to deeper layers when water is present. A cycle of shrinkage and swelling phenomena will occur that causes the soil to undergo great amount of volume changes. This movement in the soil results in structural damages especially in lightweight structures such as sidewalks, driveways, basement floors, pipelines and foundations. Expansive soils generally called as Black Cotton Soils covers nearly twenty percent of the geographical area in India. Prasad et al. [1] concluded that montmorillonite mineral is predominant in expansive soil based on differential thermal analysis and X-ray diffraction pattern analysis test. These soils contain high percentages of clay with predominant montmorillonite mineral in it causing the soil to swell and shrink during drying and wetting. The nature of these soils creating a problem to the civil engineering structures particularly flexible pavements constructed on them. Many Highway agencies, private organizations and researchers are doing extensive studies on this problem and its remedial measures. Katti et al. [2] studied the properties of black cotton soils in place can be altered by treating with aqueous solution of KOH.

Sivanna et al. [3] enumerated that with the addition of CaCl2 & KOH to the expansive soil, an increase in strength and reduction in swelling was observed. The aluminum was used into the soil which caused precipitation into the pore space and strengthening the soil [4-5]. Some of the researchers used different types of chemical such as Potassium Chloride (KCl), Calcium Chloride (CaCl2) and Ferric Chloride (FeCl3) effectively in place of lime, because these chemicals are dissolvable in water making it to mix easily with

[156] Behaviour of Black Cotton Soil and Remedial Measures soil and supply adequate cations [6-7]. Singh and Das [8] used Sodium Chloride (NaCl) as a stabilizer to expansive soil and results shown that the CBR, UCS and indirect tensile strength of was greatly improved. Eisazadeh et al. [9] used the lime for the treatment of expansive soils is calcium based stabilizers which is widely used in the world. Mishra [10] investigated that the property of black cotton soil effectively improved by use of different percentage of lime contents. In India, black cotton soils have liquid limit values ranging from 50 to 100%, plasticity index ranging from 20 to 65% and shrinkage limit from 9 to 14%. The amount of swell generally increases with increase in the plasticity index. The swelling potential depends on the type of clay mineral, crystal lattice structure, cation exchange capacity, ability of water absorption, density and water content.

2. MATERIALS AND METHODS

Table 1: Engineering Properties of Black Cotton Soil Properties Values Liquid limit 56.8% Plastic limit 20.5 % Specific gravity 2.68 Maximum Dry density 1.72 gm/cc Optimum moisture content 19.65% Free swell index 80 % Natural water content 10.8 %

2.1 Black Cotton Soil Black cotton soil is obtained from the site after removing the upper surface containing organic compound near new ISBT Bairiya Patna. The engineering properties of soil are obtained in the laboratory of NIT Patna.

2.2 Sand, Lime and Cement The Sone river sand is obtained from the Koilwar, near Bihta. Lime obtained from the local market, and cement is (IS 8112-1989) 43 grades OPC used.

2.3 Laboratory Tests A series of laboratory tests consisting of specific gravity, grain size distribution using sieve analysis and hydrometer analysis, specific gravity, compaction, free swell index have been conducted on black cotton soil. Additives used are sand, lime and cement with different percentage.

2.4 Specific Gravity Test IS 2720-3-1 (1980) part 3 standard test methods for specific gravity determination for soil, sand, lime, cement have been used.

2.5 Grain Size Distribution Test IS code IS 2720-4 standard has been practiced for classification of soils using sieve analysis and hydrometer analysis.

[157] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.6 Compaction Test Proctor tests were conducted in accordance with IS 2720-8 (1983). Soil and glass waste used in compaction passed from 4.75 mm sieve. The compaction mould sizes which were used of 101 mm diameter and 125 mm height.

2.7 Free Swell Index IS: 2720(Part 40)-1985 standard test method for free swelling index is used for black cotton soil and admixture.

3. RESULTS AND DISCUSSION

3.1 Compaction Characteristics A series of compaction tests were performed first on locally available black cotton soil passing 4.75 mm sieve with varying water content to determine the optimum moisture content and the maximum dry density. Fig. 1 shows the compaction characteristics of black cotton soil, cement, lime and sand. Table 2 shows the maximum dry density and optimum moisture content of the soil and admixtures. The results of compaction test shows that the maximum dry density increases with the addition of admixtures. The maximum dry density obtained for cement is highest among the entire admixture used. The optimum moisture content decreases with the addition of admixtures. The maximum decrease in optimum moisture content is observed in case of sand.

Table 2: Maximum Dry Density and Optimum Moisture Content of Soil and Admixtures Material Optimum Moisture Content (%) Maximum Dry Density (gm/cc) Black cotton soil 19.65 1.72 Cement 16.5 2.02 Lime 14.57 1.86 Sand 13.53 1.8

2.2

Black cotton soil

2 Lime

Cement

Sand 1.8

Dry density (gm/cc) density Dry 1.6

1.4 10 14 18 22 26

Water content (%)

Fig. 1: Variation of Dry Density and Moisture Content for Different Soil-foundry Sand Mixes [158] Behaviour of Black Cotton Soil and Remedial Measures The admixture sand, lime and cement mixed in the ratio of 94 % (soil) : 6 % (admixture). The maximum dry density and optimum moisture content are obtained from the graph shown in table 2. Fig. 2 shows the swelling characteristics of black cotton soil and addition of admixture at 6%. Results show that maximum decrease in welling characteristics with the addition of cement because of better pozzolanic action and cations exchange capacity. Table 3 shows free welling index of black cotton soil and admixture at different percentage. It is found that free swell index is low for cement which may be due to low cations exchange capacity.

100%

80%

60%

40% Free swelling (%) Free index 20%

0% Black cotton soil Black cotton soil Black cotton soil Black cotton soil + 6% sand + 6% lime + 6% cement

Fig. 2: Free Swelling Index of Black Cotton Soil and Admixtures

Table 3: Free Welling Index of Black Cotton Soil and Admixture Free Swelling Index (%) Material Sand Lime Cement Black cotton soil + Admixture 2% 68 64 57 Black cotton soil + Admixture 4% 54 53 48 Black cotton soil + Admixture 6% 55.5 48 40.5 Black cotton soil + Admixture 8% 44.5 42 37 Black cotton soil + Admixture 10% 43 40 35

4. CONCLUSIONS ●● It is found that free swell index (%) of black cotton soil decrease when the admixtures are mixed with it. Initially, free swell index of black cotton soil (no admixtures mix) was 80%. After the mixing of 6% amount of lime, cement, and sand in the black cotton soil, free swell index decreases respectively upto 48%, 40.5%, and 55.5%. It is also observed that with cement, the soil shows the least free swell index. Hence, it is suggested that the swelling behaviour of expansive soil can be reduced by mixing soil with stabilizers.

[159] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) ●● The properties of the black cotton soil are improved by the addition of cement, lime and sand. ●● From the above performed experiment it is found that 6% is the optimum value of admixture that needs to be added to the soil for best result in the field. ●● Swelling index is minimum for cement followed by lime and sand. ●● From standard proctor test we found that the value of MDD is maximum for cement followed by lime and sand.

REFERENCES [1] Prasad, DSV., Raju, Dr GVRP. and Murthy, VR., Use of Waste Plastic and Tyre in Pavement System, The Institution of Engineers India Journal, Vol. 89, 2008, 31-34. [2] Katti, R.K., Kulkarni, K.R. and Radhakrishnan, N., Research on Black Cotton Soils without and with Inorganic Additives, Indian Road Congress Road Research Bulletin, No. 10, 1966, 1-97. [3] Sivanna, G. S., Strength and consolidation characteristics of black cotton soil with chemical additives – CaCl2 & KOH, report prepared by Karnataka Engineering Research Station, Krsihnarajasagar, India. 1976 [4] Gray, D. H., Electrochemical Hardening of Clay Soils, Geotechnique, 20(1),1970, 81-93. [5] Ozkan, S., Gale, R. J. and Seals, R. K., Chemical Stabilization of Kaolinite by Electrochemical Injection, Proceedings of Sessions of Geo-Congress, ASCE, 1998, 285-297. [6] Sivapullaiah, P.V., Role of electrolytes on the shear strength of clayey soils, Proceedings of Indian Geotechnical Conference, 1994, Warangal, India, 1994, 199-202. [7] Prasada Raju, GVR, Evaluation of flexible pavement performace with reinforced and chemical stabilization of expansive soil sub grades, Doctoral Thesis, Kakitiya University, Warangal, A.P. India, 2001. [8] Singh, G. and Das, B. M., Soil Stabilization with Sodium Chloride, Transportation Research Record, 1999, 46-55. [9] Amin Eisazadeh, (2012), Solid-state NMR and FTIR studies of lime stabilized montmorillonitic and lateritic clays, Journal of Applied Clay Science, volume 67-68, 2012, 5-10. [10] Brajesh Mishra “A Study on Engineering Behavior of Black Cotton Soil and its Stabilization by Use of Lime” International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 Impact Factor (2014): 5.611

[160] Performance Analysis of At-grade and Grade Separated Intersection using Microscopic Simulation

Atul Soni1, Deepak Varshney2, Anand Prabhat Verma3 and Nakul Gupta4 1,2Assistant Professor, Department of Civil Engineering, GLA University, Mathura, India 3,4M.Tech.Student, Department of Civil Engineering, GLA University, Mathura, India E-mail: [email protected], [email protected], [email protected], [email protected]

ABSTRACT Traffic congestion is the prime consideration for design engineers to consider. National highways are being widened to accommodate the increased traffic on roads. Also National Highways are being elevated within the city premises to provide undisturbed flow. A crowded intersection may be improved by using grade separated intersection. Performance of these intersections could be evaluated using theoretical methods or simulation based upon mathematical models. VISSIM is a microscopic, and behavior based simulation model developed to analyze the full range of functionally classified roadways and public transportation operations. Common applications of these packages include freeway and arterial corridor studies, sub-area planning studies, evacuation planning, freeway management strategy development, environmental impact studies, Intelligent Transportation Systems (ITS) assessments, current and future traffic management schemes etc. Results of simulation can be interpreted in different ways. In this study, an effort has been made to compare the effect of constructing a flyover on a congested staggered intersection on NH 2 in Mathura District. Problems were identified for the selected intersection, also various factors like Queue length formation, LOS, delay at intersections, stop average, etc were compared for the both conditions i.e. at-grade intersection vs grade separated intersection. Keywords: Traffic Simulation, At-grade Intersection, Grade Separated Intersection, VISSIM

1. INTRODUCTION Quality of traffic service is measured using Level of service (LOS) which is a qualitative measure. LOS is used to analyze traffic condition pf highways by categorizing traffic flow and assigning quality levels of traffic based on performance measure like speed, density, etc. Level-of-Service (LOS) of a traffic facility is a concept introduced to relate the quality of traffic service to a given flow rate. Level-of-Service was introduced by HCM (Highway Capacity Manual) to denote the level of quality under different operation characteristics and traffic volume. HCM proposed LOS as a letter that designate a range of operating conditions on a particular type of facility. LOS is categorized into six letters as defined by HCM, namely A, B, C, D, E, and F, where A denote the best quality of service and F denote the worst. These definitions are based on Measures of Effectiveness of that facility. Conventional measure of effectiveness include speed, travel-time, density, delay etc. There will be an associated service volume for each of the LOS levels. A service traffic volume or service flow rate is the maximum number of vehicles, passengers, or the like, which can be accommodated by a given facility or system under given conditions at selected location. VISSIM is a microscopic, time step and behavior based simulation model software developed to analyze the full range of functionally classified public transportation operations and roadways. Common applications of these packages include highways and arterial road studies, sub-area planning studies, highway management strategy development, environmental impact studies, Intelligent Transportation Systems (ITS) assessments, current and future traffic management schemes etc. Results of simulation can be interpreted in different ways.

[161] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 2. RESEARCH OBJECTIVES The LOS concept is used for highways in an era of rapid expansion, in the use and availability of the private motor car. The primary concern is congestion, and it is commonly held that only the rapid expansion of the road network would keep congestion in check. LOS can also be applied to surface streets, to describe major signalized intersections. A crowded four-way intersection where the major traffic movements were conflicting turns might have an LOS D or E. At intersections, queuing time can be used as a parameter to measure LOS; computer models given the full movement data can spit out a good estimate of LOS.

3. LITERATURE REVIEW G. Gomes, A. May, and R. Horowitz outlined a complete methodology for constructing and calibrating a simulation model of a unidirectional freeway with on ramp control. This study has shown that VISSIM simulation environment was well suited for such road way studies involving complex interactions. M. Fellendorf and P. Vortisch used both microscopic calibration and macroscopic validation, and results showed that simulation tools based on the psycho-physical car-following model can reproduce traffic flow very realistically under different real-world conditions. Therefore, it is possible but also necessary to adapt the model to the local traffic situation; at least national traffic regulations and driving styles must be taken into account. B.B. Park and J.D. Schneeberger paper proposed a procedure for microscopic simulation model calibration and validation and demonstrated the procedure through a case study. The proposed procedure appears to be effective in the calibration and validation for VISSIM for signalized intersections. W. Burghout, J. Wahlstedt using VISSIM to simulate the area with the three signal controlled intersections and MEZZO to simulate the surrounding Stockholm network. The results show the improvements of the new control scheme, but more importantly, they illustrated the usefulness of the hybrid approach for such types of applications.

3.1 Selection of Problem Traffic congestion can have several causes. Some are predictable such as traffic during daily peak hours and some less predictable such as weather or accidents. Delays caused by peak hour traffic congestion constitute the majority of traffic congestion delays. The presence of conflict points at intersections cause the traffic congestion and causes major delay in the journey. On any road network intersections are the major cause of delay and congestion. Intersection should be well designed to allow smooth traffic flow at intersections. This study includes the study of an intersection on NH 2 in district Mathura and compares the results of work done by the NHAI to improve the conditions of the intersection.

3.2 Scope of the Study India has been developing the new roads and improving the old road network to hold the need of increasing traffic on indian roads. This study is an effort to establish the relationship between the road network that has been improved to caary increased traffic. The main objective of this study is to analyze the two different situations: 1) Before the NHAI transformed an at grade intersection into a grade separated intersection and 2). After the intersection was transformed into grade separated intersection and its effect on traffic.

4. METHODOLOGY In this study a location on a NH 2 in Mathura district was selected and studied. This intersection at “Chattikara” connects the holy land of Vrindavan to the Govardhan while crossing through the NH 2 [162] Performance Analysis of At-grade and Grade Separated Intersection using Microscopic Simulation connecting Delhi with Agra. Traffic data was collected and models were developed for both conditions of the intersection. Simulations were run for each conditions to evaluate the effect of transformed intersection on traffic movement. Traffic Volume at Selected Intersection: ADT were collected for the site and average traffic volume at intersection was used for the study. Dynamic parameters were also used for the model to match the patterns of average indian driving conditions and habits of drivers. Like diamond merging, spacing of vehicles at stop and lateral clearances, etc.

Fig. 1: Traffic Volume at Intersection

Fig. 2: Modelling of At-Grade Intersection on VISSIM

[163] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 3: Modelling of Grade Separated Intersection on VISSIM

Fig. 4: Simulation Run of At-Grade Intersection on VISSIM

Fig. 5: Simulation Run of Grade Separated Intersection on VISSIM [164] Performance Analysis of At-grade and Grade Separated Intersection using Microscopic Simulation 5. RESULTS AND CONCLUSIONS Study showed that the construction of grade separated intersection has reduced the problem of traffic congestion at the selected intersection. The LOS has been improved to level D from the level E. And also the average length of Queue formation at the intersection has reduced by huge 41%. The delay average at intersection has reduced by 53% and average number of stops required by any vehicle has been reduced to 4, reduced by 69%. Average speed of the vehicles passing through intersection has been improved to 24 Km/ph, which is a significant improvement by 50%. Assuming that average fuel consumption of standard passenger car fuel consumption at intersection has also reduced due to lesser number of stops and time lost at intersection. There is a significant 25% lesser fuel requirement at the intersection which is a huge improvement over the condition of intersection at former stage.

Table 1: Results of the Study Parameters Unit At-grade Intersection Grade Separated Intersection % Change Queue Length Meters 331 195 –41 LOS – E D – Fuel Consumption Ltr/Day 134.3 100.6 –25 Delay Avg Seconds/Vehicle 185 87 –53 Stops Avg Number 14 4 –69 Speed Avg Km/hr 12 24 +50 It was concluded from the study that the construction of grade separated intersection has relaxed the traffic congestion of the selected site and it has also eased the movement of passengers crossing the intersection. Construction of grade separated intersection is also helping in reducing the pollution.

ACKNOWLEDGEMENT All the simulation related work was done on PTV VISSSIM 10 (Student) Software package.

REFERENCES [1] G. Gomes, A. May, and R. Horowitz, “Congested Freeway Microsimulation Model Using VISSIM”, Transportation Research Record 1876:71-81, (2004). [2] M. Fellendorf and P. Vortisch, “Validation of the microscopic traffic flow model VISSIM in different real-world situations”, Transportation Research Board, (2001). [3] B.B. Park and J.D. Schneeberger, “Case Study of VISSIM Simulation Model for a Coordinated Actuated Signal System”, Transportation Research Microscopic Simulation Model Calibration and Record 1856:185-192, (2003). [4] W. Burghout, J. Wahlstedt, “Hybrid Traffic Simulation with Adaptive Signal Control”, Transportation Research Record 1999:191–197, (2007).

[165] Seepage Analysis of Railway Earthen Embankment in Mokama using RFEM to Study the Effect of Varying Hydraulic Conductivity

V.K. Singh1 and A. Burman2 1M.Tech. Student, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected]

ABSTRACT In this study, seepage through the body of an earthen embankment for construction of railway lines in Mokama in Bihar is estimated using finite element method. Seepage of water through the body of earthen embankment adversely affects its stability. In order to check the reliability of the constructed railway embankment stretching for a long distance, Random Finite Element Method (RFEM) originally developed by Griffiths and Fenton (1996) is used. The influence of changeability in the spatially distributed hydraulic conductivity/permeability of the embankment material is investigated by carrying out seepage analysis. Local Averaging Subdivision (LAS) technique is used to build the random field of hydraulic conductivity of soil domain under consideration. Afterwards, Monte Carlo Simulation is performed for

1000 such random fields. The mean of total flow rate (mQ ), mean of logarithmic of total flow rate (mln Q ) 2 and variance of logarithmic of total flow rate (sln Q ) from seepage analyses of 1000 realizations of random field are reported. The results show that as the correlation length decreases, the output parameters mQ, 2 mln Q and sln Q follow a decreasing trend and vice versa. Keywords: Hydraulic Conductivity, Seepage Analysis, Random Finite Element Method, Earthen Rail Embankment, Monte Carlo Simulations, Local Average Subdivision (LAS) Method

1. INTRODUCTION A typical earthen road or railway hill resting over a plain surface may be subject to numerous external loadings throughout its life. Loadings on the embankment may occur due to dynamic loading of the vehicle travelling above the embankment or due to earthquake or due to floods. Common modes of failure in an embankment are overtopping, or due to unnecessary seepage through the embankment body, or due to excessive settlement of the embankment foundation or may occur due to slope failure of the embankment. Therefore, seepage analysis is an integral part to check the safely and reliability of an earthen embankment. The calculation of flow rate throughout an earthen embankment is complex because the position and the contour of the free surface is not well known and is calculated iteratively. Location of free surface from calculated potential heads is studied by Smith and Griffiths (2004) using finite-element method. For the analysis of both saturated and unsaturated soil Lacy and Prevost (1987), have suggested a fixed-mesh. The analysis approach of Smith and Griffiths (2004) is taken here, due to its simplicity, and also some modifications is done to improve convergence. Griffith and Fenton (1996) developed random finite element method to consider the variability inherent in the physical world. Here, Monte Carlo Simulations are performed for finite element models of any random fields for sufficiently large number of times. The random fields are generated by using a variety of techniques such as Turning Band Method, Fast Fourier Transform, Local Averaging Subdivision (LAS) technique among many others. [166] Seepage Analysis of Railway Earthen Embankment in Mokama using RFEM to Study the Effect of Varying Hydraulic Conductivity A railway earthen embankment is built in the district of Mokama in Bihar. The samples are collected from the field and tests are carried out in the geotechnical laboratory of NIT Patna. The mean and standard deviation of the hydraulic permeability is used in the software RDAM2D developed by Fenton and Griffiths (2004). The random field of hydraulic conductivities for the embankment domain under consideration is generated by LAS method. The results show that RFEM is a very efficient method to investigate the effect of spatial variability of random field in seepage analysis of earthen embankments.

2. METHODOLOGY Random finite element (RFEM) is being used in the present study to investigate the effect of spatial variation of hydraulic conductivity of soil domain under consideration in seepage analysis. Seepage equation is solved using finite element method in two dimensions. A brief description of various terms used in RFEM is provided below.

2.1 Finite Element Model In a two-dimension, four nodded isoparametric finite components in the square form can be used to discretize the domain. Hydraulic head can be calculated at the nodes of the finite element components. Also, at various nodes across the solution domain we have got an estimate of the hydraulic head of a finite-element analysis of a steady seepage problem. Generally to get the more accuracy of the solution, the number of elements should be increase. In all numerical approach, a relationship is necessary between accuracy and computer time. Here we can say that the main target of the FEM analysis is to generate a fine mesh to get require accuracy. The form of Laplace’s equation which arises in geomechanics to represent steady state flow is

∂∂22φφ kkxy+=0 (1) ∂∂xy22 where φ is the fluid total head or ‘potential’ and kx and ky are permeabilities of the medium in the x- and y-directions respectively. A set of equilibrium-type matrix can be obtain from the finite element discretisation process by reducing the differential equation, as follows

kqc {φ} = { } (2) where kc is the symmetrical ‘permeability matrix’, {φ} is a vector of nodal potential or total head values and{q} is a vector of nodal inflows or outflows. In this study, 4 noded isoparametric finite elements have been used for discretizing the domain of interest.

2.2 Covariance Function In probability theory and statistics, how much two variables are changes together can be measured by covariance. The covariance function explains the spatial or temporal covariance of the random variable process or field. In two dimensional cases, covariance function is defined as follows,

C(s',s*) = Cov X( s') , X( s*) = E X( s') X ( s*) − µµXX( s') ( s*) (3) where µX (s) is mean of X at the position s . Since the size of the variance of X (s') and X (s*) greatly affects the magnitude of the covariance, it gives us little about the degree of linear dependence between X (s') and X (s*) . Covariance can be shown more accurately with the help of correlation function which is described in Section 2.4 of this paper. [167] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.3 Variance Function Smooth functions which depict the variance of a random quantity as a function of their mean is called as the variance function. Each and every engineering property is in fact property of a local average of some sort. The Variance Function can be defined as follows

2 Var[ XT] = E( X TX( t) − µ ) (4) T where, T is the length over which random quantity is averaged at any time t. Since µ = mean = µ XT X

11tT++22tT XTX−µ = Xd(ξ) ξµ−=X X{ξ} − µX d ξ T TT∫∫tT−−22tT (5) and so that,

TT 1 2 Var XTX( t) = C(ξ −= η) d ξη d σ X γ( T ) (6) T 2 ∫∫ 00

τ= ξη − τ ρτ( ) Where , CX ( ) is covariance function of X (t) and X is correlation function of X (t) as 2 CX (τ ) = σρXX( τ). In expression (6), γ (T ) is known as variance function. For more details, please refer section 3.4 of the work by Fenton and Griffiths (2002). In our case the problem is two dimensional and for two dimensional case variance function can be described as follows,

22   θθ 2T1 22 TT 12  2 T 2  γ (TT, ) =12 +−exp −×+− 1 exp   − 1 (7) 12 22 θ θθ θ 4TT11 1 12  2 

2.4 Correlation Function Markov property tells us that the future is only affected by the presently known state. It is commonly used because of its simplicity. Also we know that the Markov correlation function in two dimensions has the form,

2 22ττ12   ρτ( 12, τ) =−+=− exp ( τ1 τ 2) exp   exp −  (8) θ θθ12  

where, θ1 and θ2 are correlation lengths.

τ1 and τ 2 are spatial lag vector components.

2.5 Correlation Length

The irregularity of a random field is measured by correlation length (θ ). In other words, it can be said that, it is the distance within which points are notably correlated. We can obtain the value of Correlation length (θ ) by calculating the area under the correlation function. ∞ θ= ∫ ρτ( )d τ (9) −∞

[168] Seepage Analysis of Railway Earthen Embankment in Mokama using RFEM to Study the Effect of Varying Hydraulic Conductivity

In the present study, θ is used. In practice, is quite similar in magnitude as the correlation ln K θln K θ length in real space. Therefore, θ and ln K have been used interchangeably in present study. Also, nondimensionalized correlation length has been as defined in RFEM software. Therefore, correlation length is nondimensionalized by dividing it by the height of the embankment H which is expressed as follows: θ θ = ln K (10) H

2.6 Local Average Subdivision Method Flow through embankment for a given permeability field realization can be calculated using a two- dimensional iterative finite-element model using program 7.3 developed by Smith and Griffiths (2004). In this study, a model with 16 elements have been used in each direction that is total 256 elements have been used. Since the sizes of the elements change during iterative process and their local average properties are similar in final mesh, local average random-field generators are preferred over point process generator. Local mean process can be processed by LAS in top to down recursive way as shown in Figure 1. In first stage, that is in stage 0, a global mean is used for the process. In stage 1, the field of the stage 0 is further subdivided into two areas whose “local” averages must be the mean to the global value. In the similar way further divisions are done and generated the values for resulting two fields while keeping upward similar. Also it should be noted that the global mean must remain constant throughout the subdivisions.

0 Stage 0 Z1

1 1 Stage 1 Z1 Z2

2 2 2 2 Stage 2 Z1 Z2 Z3 Z4

3 3 3 3 3 3 3 3 Stage 3 Z1 Z2 Z3 Z4 Z5 Z6 Z7 Z8

Stage 4

Fig. 1: LAS Construction of Local Average Random Process by Top-down Approach Source: Fenton and Griffiths, 1992

2.7 Monte Carlo Simulations Since in practice, the use of the analytical solution is limited, the analysis of practical geotechnical problems generally needs suitable numerical models, which frequently uses finite FEM to discretize the soil domain. Here for our study, to execute stochastic simulations of seepage across the embankment, FEM is united together with Monte Carlo analysis. A large number of finite element models (realizations) are analyzed in Monte Carlo analysis. The geometry and boundary conditions of each realization should be similar but having similar probability density functions with different arbitrary spatial distributions of material properties. To understand the uncertainty in Monte Carlo Analysis, a large number of finite element models are solved in which each model is similar to different random spatial configuration of soil properties. [169] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 3. RESULTS AND DISCUSSION In this study, the earthen railway embankment of height 12 m and having base width of 66m and top width 12 m (refer to Figure 2) is analyzed. Soil samples were collected from Mokama and tested in geotechnical laboratory in NIT Patna. The permeability of the soil samples are determined from laboratory tests. The permeability data is used as input data in RFEM analysis. The coefficient of permeability of the soil in both x and y direction assumed to be same i.e. kx=ky.

Fig. 2: Geometry of the Embankment Then the flow rate statistic for the earth embankment is calculated for a range of the statistical parameters of permeability (K). Here, the estimated standard deviation and mean of the total flow rate, (sQ ) and (mQ ) is computed for σµKK= [0.1, 0.5, 1.0, 2.0, 4.0, 8.0] and θln K = [0.1, 0.5, 1.0, 2.0, 4.0, 8.0]. Also to calculate this 1000 realizations is averaged for each value. To verify trends at large correlation lengths an µ additional run for θln K = 16 is performed for the embankment. In this study, the value of K is fixed at 1. After 1000 analyzing realizations, a flow rates frequency density plot for each set of parameters of K(x) have been obtained. Histogram obtained is shown in Figure 3, where fitted lognormal distribution is superimposed.

Fig. 3: Flow Rate Frequency Density Plots The estimators for the lognormal distribution are as follows

[170] Seepage Analysis of Railway Earthen Embankment in Mokama using RFEM to Study the Effect of Varying Hydraulic Conductivity

n 1 mQln Qi= ln (11) n ∑ i=1

n 1 s22= (lnQm− ) (12) ln Qn −1 ∑ iQln i=1

2 mln Q s where Qi, and ln Q are total flow rate, mean of log flow rate and standard deviation of log flow rate through the ith realization respectively and n is the no. of realizations. 2 The expected mean and variance of the total log-flow rate, represented as mln Q and sln Q, respectively, are

σ 2 σ 2 =ln 1 + K function of the variance of log-permeability, ln K 2 and the correlation length, θln K ,where µK is µK mean and σ K is standard deviation of permeability. 2 The permeability K(x), is assumed to follow a lognormal distribution, with mean µK, variance σ K, and parameters µln K and σln K, where

σ 2 σ 2 =ln 1 + K (13) ln K 2 µK

1 µ=ln ( µσ) − 2 (14) ln KK2 ln K In this study, the output quantities have no dimension. For the flow rate, by forming the product of the global conductivity matrix and the potentials, global flow vector q is computed as shown in Eq. 2. The non dimensional flow rate Q defined by Q Q = (15) ∆×H µK where H is the total head difference between the up-and downstream sides and µK is the mean permeability.

2.00E-04 ϴ=0.1 1.80E-04 ϴ=0.5 1.60E-04 ϴ=1 1.40E-04 ϴ=2 ϴ=4 1.20E-04 q ϴ=8 m 1.00E-04 ϴ=16 8.00E-05 6.00E-05 4.00E-05 2.00E-05 0.00E+00 0 1 2 3 4

2 σ lnK

Fig. 4: Estimated Mean Flow Rate through Embankment

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2 It can be seen from Figure 4, the value of mean flow rate decreases on increasing σln K . The reduction is more prominent for the lower value of correlation lengths but when the correlation length value is more than the length of embankment it virtually disappears. During seepage, very less permeability is encountered along the path, which greatly affects the total flow rate. The chances of getting a small-permeability or “blocked” spaces increases on increasing the variance of the permeability for small correlation length, resulting in a decreasing mean flow rate. It is a known fact, as the value of anything decreases or increases, then the value of their logarithm will 2 also decrease or increase respectively. Since the mean flow rate decreases on increasing σln K, therefore the 2 value of mean of log flow rate also decreases on increasing the value of σln K. Fig. 5 show the variation of mln Q values for 1000 realization with varying correlation lengths. It is observed that as the correlation length θ increases, mln Q from 1000 realizations also decreases. If θ decrease, mln Q values are found to follow an increasing trend. Therefore, it can be said mln Q and θ are inversely proportional to each other.

0 1 2 3 4 -8 ϴ=0.1 ϴ=0.5 ϴ=1 ϴ=2 -9 ϴ=4 lnQ

m ϴ=8 ϴ=16

-10

-11 2 σ lnK

Fig. 5: Estimated Mean of Log-flow Rate through Embankment

1.4 ϴ=0.1 1.2 ϴ=0.5 ϴ=1 1 ϴ=2 ϴ=4 0.8 ϴ=8 lnQ 2

s ϴ=16 0.6

0.4

0.2

0 0 1 2 3 4

2 σ lnK

Fig. 6: Estimated Standard Deviation of Log-flow Rate through Embankment

[172] Seepage Analysis of Railway Earthen Embankment in Mokama using RFEM to Study the Effect of Varying Hydraulic Conductivity

2 2 Fig. 6 shows that the variation of sln Q with respect to σln K is of increasing nature on increasing the value of θ. Also for very short correlation lengths, the variance of log flow rate is very small. Large value of θ indicates relatively uniform fields being developed in each realizations. Small values of θ indicate that the random field is more rough and the values of the parameter of interest changes within a shorter length. 2 2 Obviously, in the later case, sln Q exhibit small changes. For more uniform random fields, sln Q have greater variations.

4. CONCLUSION In this study, seepage analyses have been performed through the body of an earthen embankment for construction of railway lines in Mokama in Bihar using finite element method. The influence of spatially distributed hydraulic conductivity/permeability of the embankment material is investigated by carrying out by Monte Carlo simulation using random finite element method. Local Averaging Subdivision (LAS) technique is used to build the random field of hydraulic conductivity of soil domain under consideration. Afterwards, Monte Carlo Simulation is performed for 1000 such random fields. The mean of total flow m s2 rate (mQ ), mean of logarithmic of total flow rate ( ln Q ) and variance of logarithmic of total flow rate ( ln Q ) from seepage analyses of 1000 realizations of random field are reported. The variation of (mQ ), (mln Q )and 2 σ 2 (sln Q ) with respect to variance of permeability ( ln K ) is plotted. These plots reveal as the correlation length 2 decreases, the output parameters mQ, mln Q and sln Q follow a decreasing trend and vice versa.

REFERENCES [1] Fenton G. A., Griffiths D.V. (1997). “Risk Assessment in Geotechnical Engineering,” ASCE J. Geotech. Eng. [2] Fenton G. A., Griffiths D.V. (2008), “Risk Assessment in Geotechnical Engineering” John Wiley & Sons, Inc. ISBN: 978- 0-470-17820-1 [3] Smith I. M., Griffiths D.V. (2004). Programming the Finite Element Method, 4th edition, John Wiley and Sons, Chichester, New York. [4] http://www.engmath.dal.ca/rfem.

[173] Estimating Peak Ground Acceleration from Deterministic Seismic Hazard Analysis for Supaul District Near Bihar: Nepal Region

R. Gautam1, S. Kumar2 and A. Burman3 1,2M.Tech Student, Department of Civil Engineering, National Institute of Technology, Patna, Bihar, India 3Assistant Professor, Department of Civil Engineering, National Institute of Technology, Patna, Bihar, India E-mail: [email protected]

ABSTRACT The districts of Supaul lie near Bihar-Nepal border along foothills of Himalaya. Different attenuation relationships applicable for the Himalayan region have been used to estimate the site-specific Peak Ground Acceleration (PGA) for the Supaul region on the basis of Deterministic Seismic Hazard Assessment (DSHA) study. Seismicity data have been collected from IMD, New Delhi and forty seismotectonic sources were recognized in the region from Seismotectonic Atlas of India (GSI, 2000). Hypocentral distances have been measured using ArcGIS software. Maximum Peak ground acceleration value is found to occur for Main Central Thrust fault for the districts. Keywords: Peak Ground Acceleration, Attenuation Relationships, Supaul Districts, Bihar-Nepal Region, Deterministic Seismic Hazard Assessment (DSHA), Main Central Thrust

1. INTRODUCTION Earthquakes occur underneath the surface of the earth and discharge an enormous amount of energy. Since last few decades, India has experienced a few dangerous seismic events. Due to these events, around 60% of total territory is exposed to major seismic risk level and there is need to reduce the risk level (NDMA, 2011). The Nepal Bihar border is very tectonically active region of the world. Numerous large-magnitude earthquakes have ruptured discrete segments of this active boundary in the last two centuries.There is a requirement to estimate and study the strong ground motion parameters for areas lying in the zone V (IS 1893–2002, Part-1) of the border regions. The areas currently belonging to Madhubani and Supaul districts of the state of Bihar belong to zone V of seismic zone map as per IS 1893–2002 and had suffered major damages during catastrophic Bihar Nepal earthquake of 1934 and 1988.

2. SEISMICITY OF THE STUDY AREA AND DATA COLLECTION For the state of Bihar, 15.2% of the area comes within zone V, 63.7% within zone IV and 21.1% within zone III as per Indian Standard Code IS 1893, 2002. In the past 247 years, Bihar suffered almost 10 earthquakes of greater magnitude between 5.5-8.5 in Richter scale (M L ) frequently at the boundary of Bihar and Nepal (Burnwal et al., 2017). There is a necessity for the study of ground motions for Supaul districts lying in the zone V (IS 1893 -2002, Part -1) situated near the Bihar-Nepal border (Fig.1).

[174] Estimating Peak Ground Acceleration from Deterministic Seismic Hazard Analysis for Supaul District Near Bihar: Nepal Region

Fig. 1: Map of the Study Region Situated in Zone V (IS 1893–2002, part 1)

Source: http://www.mapsofindia.com/maps/india/natural-hazard-map. jpg

2.1 Data Collection The earthquake data collected from Indian Meteorological Department (IMD 2010) is tabulated in Table 1. It contains the data for the period of 1909 to 2011, with quake magnitude. The earthquakes are distributed over the region from Lat 26.50 N to Lat 28.80N and Long 84.100E to Long 87.00 E. It is observed that the number of earthquakes from medium to high magnitude is comparatively less in this area (Burnwal et al., 2017). Table 2 shows the details of seismotectonic sources active in this area. The detail of these data is available in the works of Burnwal et al. (2017).

Table 1: List of Earthquake Data for the Himalayan Regions (1909-2016) for Mb>4.5 (From IMD, New Delhi and Burnwal et al., 2017) MAG DEPTH SOURCE YEAR MON DATE HR MIN SEC LAT LONG (Mb) (KM) IMD 1909 2 17 0 0 0 27 87 5 – IMD 1934 1 15 8 43 25 26.6 86.8 8.3 – IMD 1934 1 16 4 59 22 28 86 5.6 – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – IMD 2016 2 5 21 50 9 27.8 85.4 5.2 10 IMD 2016 4 12 20 11 53 27.5 86.1 4.5 10 IMD 2016 4 9 18 50 14 27.6 85.2 4.5 10

[175] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Table 2: Details of Seismotectonic Sources in the Study Area (Collected from Seismotectonic Atlas of India Published by GSI, 2000) (km) o )=- w (km) GFD (km) FOR (km) FOR /3(km) z z w W W o Sl No. Source Type Fault Length L Fault Length = Rupture L M max = 5.08+1.16*log(L) Log(R 1.01+0.32*Mmax R D R D R 1 MFT RF 94.983 31.661 6.821 1.173 14.880 – 4.926 2 MCT RF 1105.78 368.596 8.057 1.568 37.009 – 7.789 3 EPT RF 170.894 56.965 7.117 1.267 18.505 – 5.395 – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – 42 NF-14 NF 56.391 18.797 6.558 1.089 12.261 5.296 – 43 NF-15 NF 63.988 21.329 6.622 1.109 12.850 5.2193 – 44 MKF SS 184.02 61.340 7.154 1.279 19.020 12.4800 –

Fig. 2: Map Showing the Location of Madhubani and Supaul in SEISAT through ArcGIS S/W (Courtesy: GSI, 2000)

3. METHODOLOGY The following procedure is used to estimate the value of PGA for the study areas using DSHA method: ●● Identification of forty seismotectonic sources within a radius of 400 km around the study area of Supaul with respect to tectonic setting and regional seismicity in Seismotectonic Atlas of India (GSI, 2000). The data were obtained from the site www.portal.,gsi.gov.in/gismap/ seismotectonicmap.

[176] Estimating Peak Ground Acceleration from Deterministic Seismic Hazard Analysis for Supaul District Near Bihar: Nepal Region ●● Seismotectonic Atlas of India comprises 1:1 million scale and 43 numbers of SEISAT sheets of maps published by various researchers of Geological Survey of India (GSI), 2000 for various regions. ●● In the Seismotectonic Atlas of India (SEISAT), the positions of Supaul are not prelocated. Therefore, measuring of closest distance from study area is not possible from SEISAT. ●● ArcGIS software is used for measurement of the distances of epicenters from the study area. In this software, positions of Supaul have been located with the help of ArcMAP programme. ●● After that, epicentral distances of seismic sources (faults) were calculated for Supaul area using measuring tool in the software. All the collected geotechnical data were projected on the Geo- referenced map of the study area by creating point shape file. ●● Depth of bed-rock level, line of faults, lineaments and ridge length/areas data were georeferenced and projected on the georeferenced seismic map with the help of Proximity toolset of Point Distance tool (ArcGIS software, version 10.3). This toolset is helps to find the distances between seismogenic sources (i.e. faults, thrusts etc.) to the site (Supaul).

●● With the help of the rupture length of faults, the maximum magnitude of an earthquake (M max ) is calculated. Then, the rupture width is estimated from the maximum moment magnitude for the respective source (Wells and Coppersmith, 1994). ●● Taking help of the assumptions made by Campbell (2003), the depth of energy release is calculated by Eq. (8). ●● With the help of all required parameters, the peak value of ground acceleration for each seismic source is estimated using different attenuation relationships proposed by earlier investigators for the Himalayan regions.

For each seismotectonic source, moment magnitude M w is calculated using the relationships between the surface rupture length (L) and earthquake magnitude for normal faults, strike-slip fault (SS) and reverse faults (Wells and Coppersmith, 1994)

M w = 5.00 + 1.22 log10 L Strike slip faults (1)

M w = 5.00 + 1.22 log10 L Reverse fault (2)

Normal faults (3)

All types of faults (4)

Rupture width Rw is computed by calculating the M w for each fault using following correlation (Wells and Coppersmith, 1994).

Log10 (Rw ) = -1.01 +0.32 M w (5) As the General Focal Depth (GFD) in this region usually lies in between 10 km to 30 km, hence The dip angle α adopted is 15° for thrust type sources and 90° for strike-slip and normal type seismotectonic sources. The Non-Seismogenic Depth (NSD) has been considered to be equal to 3 km as suggested by Burnwal et al. (2017). By using the following relationships, the depth of energy release Dz has been computed:

When (Rw < GFD), DZ = NSD + (GFD − RW / 2)sin á (6)

When (Rw > GFD), Dz= NSD +(Rw / 2)sinα (7) [177] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

The distance to the zone of energy release (De ) is estimated using the depth to the zone of energy release ( ) and the epicentral distance as follows: Dz (E p )

2 2 0.5 De = (E p + Dz ) (8)

In Table 3, different parameters (rupture length, magnitude, rupture width and depth of energy release) required for the calculation of PGA are computed by using Eq. (5) to Eq. (8). The maximum value for moment magnitude (M w ) is 8.05 and is obtained for the Main Central Thrust (MCT) and the minimum magnitude is obtained as 5.49 for Neotectonic Fault (NF 10) using Eq. (4). By observing Table 3, it can be noticed that the value of rupture width RW for MCT is maximum and corresponding value for NF 10 is minimum.

Table 3: Seismotectonic Sources and Different Parameters Required for PGA Calculation

o *Mmax 32 )=- w (km) GFD (km) FOR (km) FOR /3(km) z z w W W o Sl. No. Source Type Fault Length L Fault (km) Length = Rupture L M max = 5.08+1.16*log(L) Log(R 1.01+0. R D R D R 1 MFT RF 94.983 31.661 6.821 1.173 14.880 – 4.926 2 MCT RF 1105.78 368.596 8.057 1.568 37.009 – 7.789 3 EPT RF 170.894 56.965 7.117 1.267 18.505 – 5.395 4 MSRF RF 197.982 65.994 7.191 1.291 19.543 – 5.529 5 MSRMF RF 135.897 45.299 7.001 1.230 16.996 – 5.199 6 KNF SS 118.075 39.358 6.930 1.208 16.132 – 11.066 7 WPF-SS-1 SS 62.779 20.926 6.612 1.106 12.760 11.620 – 8 WPF-SS-2 SS 67.101 22.367 6.646 1.117 13.079 11.461 – 9 WPF-SS-3 SS 60.927 20.309 6.597 1.101 12.619 11.691 – 10 T Z RF 115.925 38.642 6.921 1.205 16.011 5.071 – The attenuation relationships which are mostly applicable to the study region of and Supaul districts are used in this study are shown in Table 4.

Table 4: Different Attenuation Relationships Used to Calculate PGA Sl. Researcher’s Justification Attenuation Relationship No. Name The relationship was derived considering Abrahamson a wide range of soil classifications and 1 and Lithehiser seismic parameters. These classifications (1989) and parameters were found suitable for the analysis of data related to present paper. The relationship is applicable to the Singh et al. 2 Himalayan region which incorporates our (1996) study area. The relationship is applicable to Central Jain et al. 3 Himalayan region which incorporates our log (a ) = −4.135 + 0.647M − 0.00142R + 0.753log R (2000) e h e study area.

Table 4 (Contd.)... [178] Estimating Peak Ground Acceleration from Deterministic Seismic Hazard Analysis for Supaul District Near Bihar: Nepal Region

...Table 4 (Contd.)

Sl. Researcher’s Justification Attenuation Relationship No. Name

The relationship is applicable to the 4 Sharma (2000) Himalayan region which incorporates our study area.

Nath et al. The relationship is applicable to our study 5 (2009) area.

4. RESULTS AND DISCUSSION The values of peak ground acceleration for the study area of Supaul have been calculated with the help of different attenuation relationships applicable for the Himalayan region. The values are shown in Table 5 Supaul districts respectively. Different parameters essential for the estimation of PGA values are tabulated in Table 3. Moment magnitude M w is computed using Eq. (1) - Eq. (4) on the basis of assumption for rupture length of fault given by Wells and Coppersmith (1994). Rupture widths Rw are estimated using Eq. (5) for all the faults. The depth of energy release Dz is computed using Eq. (6) and Eq. (7) and is further used to evaluate the value of hypocentral distance (X ) or De using Eq. (8).

Table 5: PGA Calculations using Various Attenuation Relationships for Supaul Area R Shing Nath Sl. Hypo-central Closest A&L Sharma Jain et al. Source M et al. et al. No. dist. X (km) Distance max (1989) (2000) (2009) (1996) (2000) (km) 1 MFT 234.911 234.86 6.821 0.016 0.064 0.041 0.008 0.016

2 MCT 62.324 61.838 8.057 0.116 0.347 0.226 0.157 0.12 3 EPT 39.728 39.36 7.117 0.126 0.235 0.182 0.193 0.095 4 MSRF 11.523 10.11 7.191 0.242 0.314 0.271 0.257 0.29 5 MSRMF 30.234 29.784 7.001 0.154 0.256 0.194 0.244 0.11 6 KNF 135.051 134.597 6.93 0.024 0.097 0.073 0.026 0.029 7 WPF-SS-1 99.69 99.011 6.612 0.03 0.093 0.076 0.037 0.031 8 WPF-SS-2 143.408 142.95 6.646 0.02 0.076 0.057 0.019 0.023 9 WPF-SS-3 205.956 205.624 6.597 0.013 0.059 0.039 0.009 0.015 10 D F 343.323 343.13 6.633 0.015 0.044 0.024 0.003 0.009 11 NF-1 342.378 342.11 6.121 0.013 0.031 0.016 0.002 0.006 12 NF-2 357.824 357.601 6.377 0.013 0.036 0.019 0.002 0.007 13 SS-1 325.8 325.625 6.941 0.013 0.054 0.03 0.004 0.011 14 SS-2 289.127 288.93 6.904 0.015 0.058 0.034 0.005 0.013 15 SS-3 223.262 223.015 6.833 0.019 0.066 0.043 0.009 0.017 16 SS-4 300.202 300.014 7.069 0.014 0.056 0.033 0.004 0.012 17 MBT-1 89.1173 88.88 7.724 0.069 0.206 0.153 0.078 0.067 18 G-1 197.435 197.364 7.064 0.022 0.084 0.058 0.013 0.022

Table 5 (Contd.)... [179] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

...Table 5 (Contd.)

R Shing Nath Sl. Hypo-central Closest A&L Sharma Jain et al. Source M et al. et al. No. dist. X (km) Distance max (1989) (2000) (2009) (1996) (2000) (km) 19 SF 146.958 146.865 6.594 0.025 0.072 0.054 0.018 0.022 20 Jangipur 242.432 242.142 6.569 0.013 0.052 0.033 0.006 0.013 21 GKG 306.51 306.321 6.594 0.011 0.057 0.033 0.004 0.012 22 MCT-1 95.7827 95.574 7.56 0.055 0.188 0.141 0.067 0.06 23 MCT-2 169.389 169.293 7.289 0.029 0.109 0.078 0.02 0.03 24 MBT-2 247.727 247.674 6.8 0.015 0.068 0.043 0.007 0.016 25 NF-3 320.143 319.91 5.703 0.016 0.041 0.023 0.003 0.009 26 NF-4 318.308 318.05 6.084 0.015 0.038 0.02 0.003 0.008 27 NF-5 338.806 338.63 6.912 0.017 0.054 0.03 0.003 0.011 28 NF-6 119.232 118.405 5.979 0.033 0.053 0.042 0.016 0.018 29 NF-7 115.653 114.755 5.849 0.032 0.049 0.039 0.015 0.017 30 NF-8 138.15 137.53 6.271 0.032 0.06 0.045 0.016 0.019 31 NF-9 141.54 140.741 5.581 0.024 0.036 0.026 0.008 0.012 32 NF-10 148.515 147.732 5.49 0.022 0.033 0.023 0.007 0.011 33 NF-11 150.166 149.562 6.156 0.028 0.052 0.038 0.012 0.016 34 NF-12 153.632 153.547 6.708 0.034 0.076 0.056 0.017 0.022 35 NF-13 182.427 182.351 6.582 0.028 0.063 0.044 0.011 0.017 36 RMF 154.536 154.45 7.222 0.033 0.073 0.054 0.017 0.021 37 SBF 159.69 159.613 7.062 0.035 0.083 0.061 0.018 0.024 38 NF-14 149.347 149.254 6.558 0.033 0.07 0.052 0.017 0.021 39 NF-15 140.079 139.982 6.622 0.036 0.076 0.057 0.02 0.023 40 MKF 128.272 127.664 7.154 0.028 0.117 0.089 0.032 0.035 If the computed PGA values in Table 5 are closely observed, it can be seen that the PGA estimation dependent on three parameters namely hypocentral distance (X) and closest distance (R) from the source along with the corresponding maximum moment magnitude (Mm) of earthquake applicable for the source. If hypocentral distance (X) and closest distance (R) from the source are more, then the estimated PGA is lesser. Similarly, if X and R from any source is less, the estimated PGA is higher. Also, if the applicable

Mmax is higher for any source, the estimated PGA is higher and vice versa. Therefore, Mmax is directly proportional to PGA to be estimated for any source.

5. CONCLUSION

In this paper, the seismicity data with earthquake magnitudes M b ≥ 4.5 for the period 1909-2011 (acquired from IMD, New Delhi and Geological Survey of India) have been used and also peak ground acceleration values have been determined with the help of various attenuation relationships at bedrock level. The calculated PGA values from different relationships are presented in Table-5 for Supaul area respectively. The main conclusions derived from the present work are as follows:

[180] Estimating Peak Ground Acceleration from Deterministic Seismic Hazard Analysis for Supaul District Near Bihar: Nepal Region ●● For Supaul district, the maximum PGA values obtained are 0.289g using Jain et al. (2009), 0.271g using Sharma (2000), 0.256g using Nath et al. (2000), 0.242g using Abrahamson and Lithehiser. (1989) for Munger Sahrasa Ridge fault (MSRF). Furthermore, maximum PGA values of 0.340g using Shing et al. (1996) is predicted for Main Central Thrust (MCT). ●● Burnwal et al. (2017) als estimated the PGA values for Sitamarhi area close to Bihar-Nepal Himalayan region. Sitamarhi lies very close to our study area. The present results are in tune with the PGA values obtained by Burnwal et al. (2017). By using the attenuation relationship proposed by Shingh et al. (1996), the maximum PGA of 0.262g was predicted for Main Central Thrust (MCT). In this paper also, a maximum PGA of 0.340g for Supaul area is predicted for Main Central Thrust (MCT) using Shingh et al. (1996) relationship.

REFERENCES [1] Abrahamson NA, Litehiser JJ (1989) Attenuation of vertical peak accelerations. Bulletin of the Seismological Society of America 79:549–580. [2] Burnwal ML, Burman A, Samui P, Maity D (2017) Deterministic strong ground motion study for the Sitamarhi area near Bihar–Nepal region. Nat Hazards 87(1): 237-254. [3] Geological Survey of India (www.portal.,gsi.gov.in) [4] Jain SK, Roshan AD, Arlekar JN, Basu PC (2000) Empirical attenuation relationships for the Himalayan earthquakes based on Indian strong motion data. In Proceedings of the Sixth International Conference on Seismic Zonation. [5] Jain V, Sinha R (2005) Response of active tectonics on the alluvial Baghmati River, Himalayan foreland basin, eastern India. Geomorphology 70: 339–356. [6] Sharma ML (1998) Attenuation relationship for estimation of peak ground horizontal acceleration using data from strong- motion arrays in India. Bulletin of the Seismological Society of America 88: 1063-1069. [7] IS 1893 (2002) Indian standard criteria for earthquake resistant design of structures, part 1-general provisions and buildings. Bureau of Indian Standards, New Delhi.

[181] Experimental Investigation of Batter Piles in Stratified Soil

Deepak Varshney1, Atul Soni2, Anand Prabhat Verma3 and Nakul Gupta4 1,2Assistant Professor, Department of Civil Engineering, GLA University, Mathura, India 3,4M.Tech.Student, Department of Civil Engineering, GLA University, Mathura, India E-mail: [email protected], [email protected], [email protected], [email protected]

ABSTRACT The inclination of batter piles gives them the advantage to carry greater lateral loads. Batter piles carry lateral loads primarily in axial compression and/or tension while other vertical deep foundations carry lateral loads in shear and bending, therefore batter piles, generally, have a greater capacity when subjected to lateral loading. Batter piles will be subject to smaller deformations than vertical piles of the same dimensions and material. Batter piles are particularly advantageous when there is a large unsupported pile length or in weak soils where there is little lateral support. A model study has been carried out in stratified soil deposit to investigate the performance and load deformation characteristics of battered pile groups under lateral load conditions. Lateral load was applied depending upon the disposition of the battered piles in the group. Loads in each case were applied in the direction of batter and against the batter. The behavior of different pile groups was studied. The spacing between the piles had been kept to 2.5 times the diameter of pile. The piles were arranged in planes transverse to the direction of load and were symmetrical. Battered piles having a batter angle of 30º have been used. Tests were conducted in laboratory under controlled density conditions using dry and clean sand. For simulating the reversal loading, cyclic loading was given to the arrangement and effect of embedment depth, direction of batter and group arrangement was studied on the lateral load carrying capacity. Keywords: Batter Pile, Lateral Load, Embedment Depth, Cyclic Loading

1. INTRODUCTION Vertical piles are generally used in foundations to carry vertical loads and small lateral loads. When the horizontal load exceeds the permissible bearing capacity of vertical piles, batter piles are used in combination with vertical piles. Batter piles are also called inclined piles. The degree of batter is the angle made by the pile with the vertical. If the lateral load acts on the pile in the direction of batter, it is called an in-batter or negative batter pile. If the lateral load acts in the direction opposite to that of the batter, it is called an out-batter or positive batter pile. Fig. 1.1 shows the types of batter pile.

1.1 Research Objectives The present investigation was performed to study the load deformation characteristics of battered pile groups under lateral load condition. Depending upon the disposition of the battered piles in the group, loads in each case were applied in the direction of batter and against the batter. The behavior of eight pile groups was studied. The spacing of piles at the bottom of pile cap was kept 2.5d in each case where d is diameter of the pile for testing. The piles were arranged in planes, transverse to the direction of load and were symmetrical. Battered piles having a batter angle of 30º have been used. Tests were conducted in laboratory under controlled density conditions using dry and clean sand. Vertical piles, positive and negative batter piles at 30º batter angle with vertical axis were tested with free head conditions under applied lateral loads. The experimental investigation led to load deflection curves. Attempt has been made to compare the behavior of single free head piles and the different pile groups, to understand the extent of group action in each case. [182] Experimental Investigation of Batter Piles in Stratified Soil On the basis of the entire study, conclusions were drawn about the behavior of laterally loaded flexible battered piles and pile groups. Also a thorough review of both the theoretical and experimental reports concerning single battered pile and pile groups has been performed. The behavior of the pile groups have been assessed from the literature available, in addition to those drawn from the experimental works reported.

PL PL

β=Angle of +β Batter -β

Out Batter or + (ve) In Batter or - (ve) Batter Batter

Fig. 1.1: Batter Pile

2. TEST MATERIAL AND MATERIAL USED Response under lateral load is determined with the help of load versus settlement diagrams. All the tests are conducted in a four layered sand bed, laid at uniform density by rainfall technique in specially made tank. Four different types of sands have been used in the experiments. Full scale field tests are highly desirable but the unpredictable nature of soil and the adjoining conditions along with the involvement of large sums of funds restrict the use of these tests. In the absence of testing prototype, small scale laboratory model tests conducted on model pile groups in a foundation medium prepared under controlled conditions may serve the purpose to some extent. However, it should be noted that the limitation like scaling effect is inherent in such studies. Such studies can help in understanding the related phenomenon associated with such problems and in developing rational semi-empirical models to predict the load capacity. The results obtained from the model tests can possibly extend through non-dimensional quantities and it is relatively easy to control the parameters influencing the behavior of vertical piles and batter piles both individually and in group arrangement while model testing. In addition, the funds involved in carrying the study are quite less as compared to the field tests. The relevant parameters considered for study are ●● Embedment length to diameter of the pile ratio (L/D) ●● Pile spacing (s) ●● Angle of batter ( ) ●● Orientation of batter β ●● Pile group configuration ●● Soil properties

2.1 Foundation Medium The sands used in the model test were locally available in the market. Popular names are quoted in bracket. The particle size distribution curves of the sands are shown in Figure 2.1, 2.2, 2.3 and 2.4. According to the Indian Standard on classification of soils for general engineering purposes (IS 1498:1970), the classification of soils are presented in Fig. 2.1, 2.2, 2.3 and 2.4

[183] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Table 2.1: Properties of Sand 1 (Red Dust) Sr. No. Properties Values 1 Effective size 0.155 2 Uniformity coefficient (Cu) 2.4 3 Coefficient of curvature (Cc) 0.89 4 IS classification SP (Gap Graded) 5 Passing 1.18mm IS sieve 94.03 6 Specific gravity (G) 2.85 7 Dry Density 14.79 kN/m3

Fig. 2.1: Sieve Analysis of Sand 1 (Red Dust)

Table 2.2: Properties of Sand 2 (Yamuna Sand) Sr. No. Properties Values 1 Effective size 0.135 mm 2 Uniformity coefficient (Cu) 2 3 Coefficient of curvature (Cc) 0.97 4 IS classification SP (Gap Graded) 5 Passing 1.18mm IS sieve 98.73 % 6 Specific gravity (G) 2.76 7 Dry Density 15.44 kN/m3

Fig. 2.2: Sieve Analysis of Sand 2 (Yamuna Sand)

[184] Experimental Investigation of Batter Piles in Stratified Soil

Table 2.3: Properties of Sand 3 (Chambal Sand) Sr. No. Properties Values 1 Effective size 0.18 mm 2 Uniformity coefficient (Cu) 2.15 3 Coefficient of curvature (Cc) 0.91 4 IS classification SP (Gap Graded) 5 Passing 1.18mm IS sieve 92% 6 Specific gravity (G) 2.82 7 Dry Density 17.6 kN/m3

Fig. 2.3: Sieve Analysis of Sand 3 (Chambal Sand)

Table 2.4: Properties of Sand 4 (Red Crusher) Sr. No. Properties Values 1 Effective size 0.192 mm 2 Uniformity coefficient (Cu) 4.67 3 Coefficient of curvature (Cc) 1.2 4 IS classification SW 5 Passing 1.18mm IS sieve 84% 6 Specific gravity (G) 2.77 7 Dry Density 18.3 kN/m3

Fig. 2.4: Sieve Analysis of Sand 4 (Red Crusher) A total of 28 experiments were conducted with pile spacing of 2.5d and pile configuration of 1×1, 2×1, 2×2, 3×3, 4×1 and 4×4. Combinations were tested for different L/d (Embedment to diameter ratio) and orientation of batter pile (30º positive and 30º negative).

[185] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Various parameters chosen for conducting the tests are: Diameter of the Pile 22mm Embedment length 550 mm; L/d = 25 660 mm; L/d = 30 Pile group 2×1, 2×2, 3×3, 4×1, 4×4 Spacing 2.5d Batter Angle 30°

3. RESULTS AND CONCLUSIONS Load v/s displacement curve obtained under cyclic loading of lateral loads are presented in following figures. For Embedment Ratio: L/d = 30

Fig. 3.1: Load v/s Displacement Curve for One Fig. 3.2: Load v/s Displacement Curve for One Positive Batter Pile Negative Batter Pile

Fig. 3.3: Load v/s Displacement Curve for 2×1 Fig. 3.4: Load v/s Displacement Curve for 2×1 Pile Group with Two Positive Batter Pile Group with Two Negative Batter

[186] Experimental Investigation of Batter Piles in Stratified Soil

Fig. 3.5: Load v/s Displacement Curve for 2×2 Fig. 3.6: Load v/s Displacement Curve for 2×2 Pile Group with two Positive Batter Piles Pile Group with two Negative Batter Piles

Fig. 3.7: Load v/s Displacement Curve for 2×2 Fig. 3.8: Load v/s Displacement Curve for 2×2 Pile Group with Four Positive Batter Piles Pile Group with Four Negative Batter Piles

Fig. 3.9: Load v/s Displacement Curve for 3×3 Fig. 3.10: Load v/s Displacement Curve for 3×3 Pile Group with Three Positive Batter Piles Pile Group with Three Negative Batter Piles

[187] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 3.11: Load v/s Displacement Curve for 4×1 Fig. 3.12: Load v/s Displacement Curve for 4×1 Pile Group with One Positive Batter Piles Pile Group with One Negative Batter Piles

Fig. 3.13: Load v/s Displacement Curve for 4×4 Fig. 3.14: Load v/s Displacement Curve for 4×4 Pile Group with Four Positive Batter Piles Pile Group with Four Negative Batter Piles Load v/s displacement curve obtained under cyclic loading of lateral loads are presented in following figures. For Embedment Ratio: L/d = 25

Fig. 3.15: Load v/s Displacement Curve for One Fig. 3.16: Load v/s Displacement Curve for One Positive Batter Pile Negative Batter Pile

[188] Experimental Investigation of Batter Piles in Stratified Soil

Fig. 3.17: Load v/s Displacement Curve for 2×1 Fig. 3.18: Load v/s Displacement Curve for Pile Group with Two Positive Batter 2×1 Pile Group with Two Negative Batter

Fig. 3.19: Load v/s Displacement Curve for 2×2 Fig. 3.20: Load v/s Displacement Curve for Pile Group with two Positive Batter Piles 2×2 Pile Group with two Negative Batter Piles

Fig. 3.21: Load v/s Displacement Curve for 2×2 Fig. 3.22: Load v/s Displacement Curve for Pile Group with Four Positive Batter Piles 2×2 Pile Group with Four Negative Batter Piles

[189] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 3.23: Load v/s Displacement Curve for 3×3 Fig. 3.24: Load v/s Displacement Curve for 3×3 Pile Group with Three Positive Batter Piles Pile Group with Three Negative Batter Piles

Fig. 3.25: Load v/s Displacement Curve for 4×1 Fig. 3.26: Load v/s Displacement Curve for Pile Group with One Positive Batter Piles 4×1 Pile Group with One Negative Batter Piles

Fig. 3.27: Load v/s Displacement Curve for 4×4 Fig. 3.28 Load v/s Displacement Curve for 4×4 Pile Group with Four Positive Batter Piles Pile Group with Four Negative Batter Piles Single positive battered piles are more resistant to lateral loads than single negative battered piles. The deflections get increased when number of cycles is increased, which is quite clear from load deflection curves (Tested for Single Cycle). It is clear that the behavior of pile groups containing batter piles mainly depends upon the disposition of the batter and the orientation of batter pile in the group, i.e. the direction of load with respect to the batter. [190] Experimental Investigation of Batter Piles in Stratified Soil Pile groups having both batter and vertical piles are more resistant to lateral loads, than a pile group containing vertical piles only. Pile group having positive batter piles are more resistant than a pile group having a similar negative batter.

REFERENCES [1] Gong Jian, Chen Renpeng, Chen Yunming, etc. Prototype testing study on micropiles under lateral loading. Chinese Journal of Rock Mechanics and Engineering, 2004, Vol 23, No.20, pp. 3541-3546. [2] Jiang Chunlin, Gao Yongtao. Study on effect of inclination to horizontal bearing capacity of anchor-piles. Transportation Science & Technology. 2007, No. 6, pp. 67-40. [3] LU Fan-ren, CHEN Yun-ming & CHEN Ren-peng, etc. Analysis of batter pile under arbitrary inclined loads in semi-infinite solid [J]. Journal of Zhejiang University (Engineering Science). 2004, Vol. 38, No. 2, pp. 191-194, 248. [4] Singh, T., Pal, M. & Arora, V.K. Int. J. of Geosynth. and Ground Eng. (2017) 3: 28. https://doi.org/10.1007/s40891-017- 0103-9.

[191] Permeability Characteristics of Different Soils Added with Natural Fibres

Nikhil Kumar Chaturvedi1, U.K. Maheshwari2 and Alok Kumar Mishra3 1,3P.G. Scholar, Department of Civil Engineering, K.N.I.T. Sultanpur, (U.P.), India 2Professor and Head, Department of Civil Engineering, K.N.I.T. Sultanpur, (U.P.), India E-mail: [email protected], [email protected], [email protected]

ABSTRACT The permeability of the soil is one of the important parameter for construction of subgrade, embankments of highways, railways etc. The fine-grained and coarse-grained soils have different water storing capacities which make them to behave accordingly in terms of permeability. This may be the reason for high compressibility effects in fine-grained soils and high erosion values for coarse-grained soils. Also, the poor shear strength and high permeability of subgrade makes it susceptible to formation of gullies and cutting edges. Literature available shows that different types of additives may be helpful to improve the strength and permeability characteristics for such cases. In this paper, an attempt has been made to investigate the effect of addition of natural fibres (jute in present case) in two different types of soils i.e. CI (soil-1) and SM (soil-2) in different proportions. The jute fibres of 1cm length have been mixed in five different proportions varying from 0 to 1% by weight (0, 0.25, 0.50, 0.75 and 1%) to study the aspects of modified permeability. Standard experimental methods as per BIS standards have been performed for classification of soils and permeability values. The experimental analysis of above mentioned soils show the opposite behaviour of change in permeability in the tested range of addition of jute fibres. The permeability values obtained for soil-1 and soil-2 increases or decreases with maximum or minimum values at 1% fibre added. Keywords: Subgrade, Permeability, Jute, Gullies and Cutting Edges

1. INTRODUCTION Transportation plays a very important role in the development of economy, industry, society and culture of any country. This provides a wider frame to expand its infrastructural facilities for further development. Economy in road networks can be achieved through economical pavement design as poor subgrade needs a modification in various factors that enhance the properties of subgrade. The stability of the road structure depends upon the strength of the on which it is constructed. For the soft or weak soils, the properties have to be improved for better performance when these soils come in contact with water. Therefore, for the enhancement of soil properties as like permeability requires new techniques of modification for enhancing the permeability and many other geotechnical properties of soils these are to be treated with different kinds of additives. The high cost of various stabilizers and synthetic materials used in the subgrade construction is leading towards high construction cost. As the synthetic stabilizers are also leading towards the problem of pollution and effecting our environment. So, all these problems led to intense global research towards economical utilization of natural sources such as jute, coir, sisal, bamboo and many others for the improvement of subgrade of roads and many other constructional activities.

2. LITERATURE REVIEW In regions where cohesive and cohesionless soils as like black cotton and silty sand are encountered, the construction of building and roads is highly risky on grounds as the soil is highly compressible, erosion prone and these soils are also susceptible for volumetric instability due to the contact of water with the soils.

[192] Permeability Characteristics of Different Soils Added with Natural Fibres Many investigators have attempted to improve the engineering behaviour of soils by mixing jute fibres and it is expected to contribute towards better road performance and achieving economy. Chegenizadeh A., Nikraz H. (2011), investigated the effect of natural fibre inclusion on the permeability of soils. Clayey sand was selected as soil part of the composite and natural fiber was used as reinforcement. The fibre parameters differed from one test to another, as fibre length were changed from 10 mm to 25 mm and fibre content were varied from 0.1% and 0.3%. For each test, permeability coefficients derived and the results were compared. The test results proved that inclusion of fibre content and length both affected the hydraulic conductivity of soil as both the increase in fibre content and length caused increase in permeability. Jain R., Agnihotri A.K. (2015), in this study the effect of polypropylene fibre inclusion in the mixture of sand was studied. It was found that it can act as a substitute for reduction in permeability of sand and at the same time gain in strength. Various permeability tests were carried out for different fibre contents in various proportions, namely at 6 mm and 12 mm fibre length. Kumar U., et al. (2016), illustrated the change in hydraulic conductivity of a clayey soil, due to addition of solid plastic waste. The study shows that specific gravity follows decreasing trend and hydraulic conductivity increase with % addition of plastic waste in the soil. Kumar U., et al. (2016), figures out that behaviour of the soil permeability is different with materials with respect to percentage and proportions of mixing. The permeability of soil is decreases with increase of RHA, stone dust and lime and increases with increase in % of PP fibre. Kumar U., et al. (2016), presented the experimental work by addition of fly ash in different proportions (0-16%) by weight of clayey soil on the permeability characteristics. The result shows that permeability is increasing with the % addition of fly ash in clayey soil. Hence based on the literature available and reported in the present work, an experimental analysis has been carried out, to understand the effect of addition of jute fibres randomly in different proportions in selected soils of different soil characteristics with fibre size (length) of 1cm (size adopted is based on literature available). Based on literature summary as discussed above, the main objectives of the present work are: 1. To experimentally determine the geotechnical properties of two soils selected soils such as specific gravity, sieve analysis, plasticity index, OMC, MDD, swelling index, CBR value and permeability and its classification. 2. To experimentally collect and analyze the data for optimum moisture content and maximum dry density of the selected Soil-1 i.e. CI Intermediate clay with the addition of jute fibres in five different proportions of selected length (0, 0.25, 0.50, 0.75 and 1% by weight). Soil-2 i.e. SM Silty sand with the addition of jute fibres in five different proportions (0, 0.25, 0.50, 0.75 and 1% by weight) of size (length) 1cm. 3. To experimentally analyze the variation in values of permeability of two selected soils (CI and SM) when added with different proportions of jute fibre (0, 0.25, 0.50, 0.75 and 1% by weight) of size (length) 1cm.

3. PHYSICAL PROPETIES OF MATERIAL USED The materials used for the present experimental work include two different nature types of soil and jute fibres. As the soils taken for the present study are of two different natures so these soils are collected from two different places. The properties of these are discussed as below: A. Soil-1: i.e. Intermediate clay (CI) was taken from Badhoi in Mirzapur district it is very much expansive in nature due to the presence of montomrillonite mineral in it. Black cotton soil due to its swelling and shrinkage properties can cause deformation of subgrades, foundations etc.

[193] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) B. Soil-2: i.e. silty sand was taken from KNIT campus, Sultanpur and in this soil shows the presence of high sand content with some content of silt. Further, to understand the characteristics of soil behaviour, the experimental data has been obtained by conducting laboratory experiments in Civil Engineering Department, KNIT Sultanpur. The data has been obtained as per the standard procedures as prescribed in respective BIS codes. The physical properties of both the soils obtained experimentally are shown in Table 1.

Table 1: Physical Properties of Soil-1 and Soil-2 Value Obtained Value Obtained Soil Properties Soil Properties (Soil-1) (Soil-2) Specific gravity, G 2.71 Specific gravity, G 2.59 Liquid limit (%) 43.12 Cu 7.5 Plastic limit (%) 25.45 Cc 1.76 Plasticity Index (%) 17.67 IS soil classification SM (Silty sand) IS soil classification CI (Intermediate clay) Gravel (%) 0 Gravel (%) 3.08% Sand (%) 1.12 Sand (%) 85.85% Silt (%) 37.88 Silt and clay (%) 11.07% Clay (%) 61 OMC (%) 13 OMC (%) 19.2 MDD (g/cc) 1.865 MDD (g/cc) 1.61 Permeability (cm/sec) 8.5185x10^-5 Permeability(cm/sec) 2.9251x10^-6

120

100

60 % finer 40

0 0.001 0.01 0.1 1 10 100 Particle size (mm)

Fig. 1: Particle Size Distribution Curve for Soil-1 and Soil-2 C. Jute Fibres: For collection of jute fibres; ropes of jute have been taken from local market of Sultanpur and then these ropes were converted in the form of fibres of desired length and thickness. The physical properties of jute fibres obtained experimentally and through study and are shown in table 2.

[194] Permeability Characteristics of Different Soils Added with Natural Fibres

Table 2: Physical Properties of Jute Fibres Jute Properties Value Obtained Alpha cellulose 60 Hemi cellulose 20 Lignin 17 Minerals, fatty & waxy substances 03 Specific Gravity 1.28 Colour Brown

4. EXPERIMENTAL DATA COLLECTED AND ANALYSIS The following experimental data i.e. OMC, MDD and Permeability is further collected for the following: 1. Soils used 2. Soil-1 i.e. black cotton soil and Soil-2 i.e. silty sand mixed with jute fibres in five different proportions. For these soils, first OMC and MDD were found for each case. Further, the permeability characteristics were determined for both the soil samples using falling head permeability test for original soil and when mixed with different proportions of jute fibres.

4.1 Soils Used The experimentally determined values for virgin soils of OMC, MDD and permeability for the soil-1 (CI) are 19.2%, 1.61g/cc and 2.9251x10^-6cm/sec respectively and for the soil-2 (SM) the values of OMC, MDD and permeability are 13.0%, 1.865g/cc and 8.5185x10^-5cm/sec respectively.

4.2 Soil Added with Jute Fibres The experimental data for both the soils is then collected for OMC, MDD and permeability values when soils are added with jute fibres in different proportions i.e. 0% to 1% (by weight) of soil. The data obtained for black cotton soil and silty sand added with jute fibres in five different proportions for OMC, MDD and permeability is shown in table 3 and shown graphically.

5. COMBINED DATA ANALYSIS AND RESULTS In this paragraph, an experimental data obtained and discussed above for selected CI and SM soils added with five different proportions of jute fibres has been analyzed in a combined way for the outcome properties such as OMC, MDD and permeability. The experimental results obtained are summarized in table 3, and analysis is presented in the coming discussions.

Table 3: Results of All Properties of Soils Added with % Jute Fibres in Different Proportions Soils % Jute Fibre OMC (%) MDD (g/cc) Permeability (cm/sec) 0 19.2 1.61 2.9251×10^-6 0.25 20 1.601 3.4366×10^-6 Black Cotton Soil (CI) 0.50 20.8 1.592 4.6564×10^-6 0.75 21.6 1.578 5.2358×10^-6 1 22.5 1.565 5.8813×10^-6 0 13 1.865 8.5185×10^-5 0.25 13.6 1.835 7.1315×10^-5 Silty Sand (SM) 0.50 15.6 1.795 6.2461×10^-5 0.75 16 1.758 5.2001×10^-5 1 16.9 1.745 4.6461×10^-5 [195] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

5.1 Compaction Characteristics 5.1.1 Optimum Moisture Content The experimental data obtained for optimum moisture content of both soils added with jute fibres at five different proportions (0, 0.25, 0.50, 0.75 and 1.0%) is shown graphically in fig. 9. From fig. 9 it can be easily seen that the optimum moisture content for jute fibre mix is constantly increasing mildly from 0 to 1% jute fibres added for both soils.

Fig. 2: Optimum Moisture Content of Different Soils Added with Jute Fibre Proportions Fig. 9 shows for all the selected soils when mixed with jute fibres that there is almost linear increase in the optimum moisture content. For black cotton soil it is from 19.2 to 22.5% and for silty sand it is from 13.0 to 16.9%. The reason for the increase in optimum moisture content may be because of the high absorbing capacity of jute fibres when mixed in soil.

5.1.2 Maximum Dry Density The experimental data obtained for maximum dry density of all soils added with jute fibres at five different proportions (0, 0.25, 0.50, 0.75 and 1.0%) is shown graphically in fig. 10. From fig. 10, it can be easily seen that the maximum dry density for jute fibre mix is constantly decreasing mildly from 0 to 1% jute fibres added for all soils.

Fig. 3: Maximum Dry Density of Different Soils Added with Jute Fibre Proportions

[196] Permeability Characteristics of Different Soils Added with Natural Fibres Fig. 10 shows that for both the selected soils when mixed with jute fibres that there is a continuous decrease in the maximum dry density. For black cotton soil it is from 1.61g/cc to 1.565g/cc and for silty sand it is from 1.865g/cc to 1.76g/cc. The reason for the decrease in maximum dry density may be replacement of more soil particles by jute fibres because of their very less specific gravity of jute fibres.

5.2 Permeability The experimental data obtained for permeability of soils added with jute fibres is shown graphically in figure 12. Fig. 12 shows that the permeability for soil-jute fibre mix increases continuously for black cotton soil (2.9251×10^-6cm/sec to 5.8813×10^-6cm/sec) and silty sand (8.5185×10^-5cm/sec to 4.6461×10^-5cm/sec) with the inclusion of jute fibres.

Fig. 4: Permeability of Different Soils Added with Different Proportions of Jute Fibres For black cotton soil there is increase in permeability with increasing jute fibre content in the soil. The percentage increase in permeability for black cotton soil is (~101%) at 1% mix in the present case i.e. higher limit. The reason for increase in permeability for this soil may be attributed to the path formed by the jute fibres as like dispersed and scattered which helps in enhancing the permeability of soil. These paths formed by the jute fibre in soil allow the flow of water through this soil. It is observed for the silty sand that there is significant reduction in permeability (83.33%) at 1% mix in present case. The decrease in permeability with increasing jute fibre content in the soil may be due to the reduction in voids of the parent soil by jute fibres which in turn will obstruct the flow path.

6. CONCLUSIONS As analysed and discussed in detail above paragraphs in for soil characteristics of individual collected soils and further these soils mixed with five different proportions by jute fibres of length 1cm from this the following conclusions may be drawn: 1. The soils chosen in present experimental work are: a. Black cotton soil (soil- 1) with high compressibility i.e. CI soil having specific gravity, liquid limit, plastic limit, plasticity index, OMC, MDD and permeability as 2.71, 43, 25, 17, 19.2%, 1.61 g/cc and 2.9251*10^-6cm/sec respectively.

[197] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) b. Silty sand (soil-2) with high content of sand i.e. SM soil having specific gravity, Cu, Cc OMC, MDD and permeability as 2.67, 7.5, 1.76,18.6%, 1.72 g/cc and 4.6564*10^-6cm/ sec respectively. 2. For both soils i.e. black cotton soil and silty sand there was continuous increase in optimum moisture content and correspondingly maximum dry density was decreasing linearly when mixed with jute fibres. 3. For black cotton soil (soil-1) and silty sand (soil-2) it was obtained that there is opposite behaviour of both soils when mixed with jute fibres in permeability of soils with increasing jute fibre content in the soil. As for the soil-1 it was observed that there was percentage increase in permeability for soil about 100% at 1% jute fibre content and for soil-2 it was observed that there was decrease in permeability about 83% at 1% jute fibre mix in the present case i.e. higher limit.

7. FUTURE SCOPE Based on the present experimentally analysed work this work further may be extended in the following directions: 1. Due to the degradation of natural fibres with time the effect of natural jute fibre can be studied by bitumen coating or plastic coating. 2. The study may be further extended for other geotechnical parameters of soil.

REFERENCES [1] Aggarwal. P. and Sharma B., “Application of jute fiber in the improvement of subgrade characteristics”, Proceedings of international conference on advances in civil engineering (2010). [2] Bairagi H., Yadav R.K. and Jain R., “Effect of Jute Fibres on Engineering characteristics of Black Cotton Soil”, International Journal of Engineering Sciences and Research Technology (IJESRT) ISSN: 2277-9655 (Feburary 2014). [3] Chandel A.S. and Kumar U., “Permeability characteristics of clayey soil added with fly ash”, International conference of emerging trends in civil engineering (ICETCE) (October 2016). [4] Chandel A.S. and Kumar U., “Utilisation of fly ash and coir geo nets in improving the geotechnical properties of clayey soil”, International journal of engineering research & technology (IJERT) ISSN: 2278-0181, Volume 6, Issue 5, (May 2017). [5] Chegenizadeh A. and Nikraz H., “Permeability Test on Reinforced Clayey Sand”, World Academy of Science, Engineering and Technology 2011. [6] Goyal P., Trivedi A.S. and Sharma M., “Improvement in Properties of Black Cotton Soil with an Addition of Natural Fibre (Coir) derived From Coconut Covering”, International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Volume 5, Issue 3 (March 2015). [7] IS 2720 Methods of Test for Soils: Part 5 - Determination of Liquid and Plastic Limit, India, (1985) [8] IS 2720 Methods of Test for Soils: Part 3 - Determination of Specific Gravity/Section 1 Fine Grained Soils, India, (1980) [9] IS 2720 Methods of Test for Soils: Part 7 - Determination of Water Content-Dry Density Relation Using Light Compaction, India, 1980. [10] IS 2720 Methods of Test for Soils: Part 4 - Grain Size Analysis, India, 1985. [11] Maurya R., Kumar U. and Gupta M.K., “Hydraulic conductivity of silty soil added with plastic wastes”, International conference of emerging trends in civil engineering (ICETCE), (October 2016). [12] Maurya R., Chandel A.S. and Kumar U., “Comparative study of various soils upon addition of different materials on the basis of hydraulic conductivity parameter”, International journal of engineering research & technology (IJERT) ISSN: 2278-0181, Volume 5, Issue 5 (May 2016). [13] Sivaraju. S.V. and Pothula. M., “Characteristic changes in sandy soil reinforced with natural fibres”, International journal of engineering trends and technology (IJETT), Volume 47 (2017).

[198] Relaibility of RSM towards Damage Identification in a Six-Storey Shear Building using Vibrational Parameters

Anjneya Kumar1 and Koushik Roy2 1M.Tech, Department of Civil and Environmental Engineering, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Department of Civil and Environmental Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT The present study aims at evaluating the efficiency of response surface methodology (RSM) towards damage identification under the effect of modeling error and noise in the system. For this purpose, a six-story shear building has been considered for the study. RS model is generated for the first three frequencies and the mode shapes. In order to introduce modeling error, the responses corresponding to each of the data sample (i.e. design matrix generated using the design of experiments (DoEs)) are randomly varied. The RS equations generated using these responses with random variations will have modeling errors. Again, noise is also introduced in the response from the actual structure to simulate the field conditions. The present study explores the capability of RSM towards damage identification under the effect of modeling errors and noise in the sample. In order to check the performance of the proposed methodology probability of false detection is evaluated. Keywords: Response Surface Methodology (RSM), Design of Experiments (DoEs), Reliability Analysis

1. INTRODUCTION In recent studies, Response surface methodology (RSM) [1] has been found to be very efficient in detecting damage in various structures. The traditional finite-element based model updating techniques are computationally inefficient and are time-consuming. Comparing with them, RSM has been found to be fast and are computationally efficient. The RSM is a regression technique in which the response surface (RS) model is generated making use of the design of experiments (DoEs). Since RSM is computationally very efficient, it is used as a surrogate model to replace the Finite-element (FE) model in the model updating step. While using vibration-based damage detection techniques the RS equation can be generated for frequencies and mode shapes. For the generation of these RS equations, first of all, insignificant parameters which not contributing towards the total variance of the model generated are sorted out. This is done using a screening experiment with a low order regression equation. After the parameters are sorted, the next step is to generate design points using DoEs [3] to develop higher order equations. DoEs generates different combinations of input parameters corresponding to which responses are obtained from the actual structure to fit a regression equation for each of the responses. For obtaining the response corresponding to these design points a numerical model of the actual structure is generated. The model thus generated may have some modeling errors, resulting in responses with some error. The modeling errors may be due to inaccurate modeling in software, variation in geometric configurations, variations in the material properties, etc. Although the model updating step tries to minimize the error, the response from the actual structure can’t be perfectly mimicked. As a result, RS equations generated will have modeling errors. Also, the noise in the measurements taken from the actual structure further affects the results. In the present study, the performance of the RSM under the effect of noise and modeling error has been evaluated. For this purpose, a six-story shear building model has been considered and reliability [199] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) of the proposed methodology towards damage identification has been explored. In order to check the performance of the proposed methodology probability of false detection is evaluated. Similar reliability evaluation needs to be carried out before using RSM for detecting damage in any structure. This will help to judge whether the proposed methodology will able to detect damage in that particular structure.

2. RESPONSE SURRFACE METHODOLOGY FOR DAMANGE IDENTIFICATION The RSM is a regression technique in which regression equations are developed between input model parameters (namely, moment of inertia, Young’s modulus of elasticity etc.) and output responses (mode shapes and frequencies). The process starts with a screening experiment where a low order regression equation is generated [2]. The screening equation can be expressed as follows:

Y= o+ 1X1+ 2X2+ 3X1X2+e (1) This can be βwrittenβ in matrixβ βform as, Y=X +E (2)

Where, Y is aβ nx1 vector of the observations, n is the number of observations, X is an n x p, p = n+1 model matrix consisting of the levels of the independent variables expanded to model form, is a px1 vector of the regression coefficients, and E is a nx1 vector of random errors. β Contribution of each of the parameters towards the total variance of the model is evaluated using this equation. This is used to screen out the insignificant parameters. For this purpose, F-test is carried out as follows:

FA= ~F0.05,k,n-k-1 (3) where, n is the number of data points and k is the number of parameters. FA and F0.05,k,n-k-1 denote the F-test value of an input parameter A and the chosen F-test criterion value, respectively. SSR and SSE are the sums of squares due to residual and model, respectively. Here, FA > F0.05,k,n-k-1 indicates that A contributes significantly to the total variance of the model. After the screening experiment is over a more detailed higher order regression equation is generated between inputs obtained after screening (namely, moment of inertia, Young’s modulus of elasticity etc) and output parameters (mode shapes and frequencies). For this purpose, design points are generated using DoEs. The final RS equation looks as shown below:

= + + + o (4) Ŷ�Where,β is the estimated response, k is the number of input parameters, and are regression coefficients.

The coefficientsŶ� of the regression can be obtained through the methods of leastβ square as follow.

T T L= =ei ei=(Y-X ) ( Y-X ) (5) Here, can finally be calculatedβ βas =(XTX)-1XTY.

For eachβ of the responses, a separateβ RS equation is generated. For the generation of the RS equations, the design points are generated through DoEs. Since the central composite design (CCD) is more popular it has been used in the present study. In order to generate design points, design bounds for each parameter are fixed at around 20 to 30 % about their mean values. Corresponding to each of the samples in the design matrix generated, responses are obtained from the numerical model. The regression coefficient is then obtained through the methods of least squares. [200] Relaibility of RSM towards Damage Identification in a Six-Storey Shear Building using ibrationalV Parameters

2.1 Central Composite Design Central composite designs (CCD) [3] can either be factorial or fractional factorial design with centre points, augmented with a group of axial points. In Figure 1 there are four corners (±1) factorial design points along with four axial (± ) star points. Depending upon the values of and how it is calculated, there are various types of the CCD, namely rotatable, face-centred, and practical. Central composite design has 2k α α k factorial points, 2k axial points and n0 centre points. Therefore, there are a total of n=2 +2k+n0 design points in CCD. (practical) is used for CCD when the number of variables are six or more.

Fig. 1: CCD with Two Factors at Two Levels

2.2 Model Checking Criteria The model generated needs to be checked for its adequacy using some of the criteria as given below [2].

R2= =1-( ), 0≤ R2 ≤1 (6)

Values of R2 should be closer to 1. The value of R2 increases with the addition of any parameter. Therefore there are other criteria that also need to be checked. R2 =1– =1– adj (7) R2 = 1– pred (8) Where, p=k+1 and PRESS refer to predicted residual error sum of squares [7]. Their values should be closer to 1 and both values should have a maximum difference of 0.2.

2.3 Damage Identification using Inverse Optimization After the model is ready a multi-objective inverse optimization algorithm is used to carry out the inverse optimization. This algorithm tries to find the input parameters corresponding to a particular response from the structures. In the present study MATLAB based ‘fgoalattain’ toolbox is used. The optimization problem can be formulated as follows: Minimize y to find x such that, F(x) -wy ≤ goal, lb ≤ x ≤ ub (9) Where,

F(x) ={ } (10)

[201] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Where, frsm and fexp are the frequencies obtained through RS equation and experiment (through structures) respectively. This is a dimensionless objective function. This algorithm is capable of carrying out inverse optimization to estimate ‘x’ that would have caused this particular response In the present study a six-storey shear building has been considered for the analysis. The stiffness values at each floor have been considered as the input parameters. The inverse optimization uses frequencies and mode shapes obtained from the healthy and the damaged structure to obtain their respective stiffness values. These stiffness values are compared to obtain damage percentage.

3. NUMERICAL STUDY FOR RELAIBILITY ANALYSIS In the present study, a six-story shear building has been considered as shown in Figure 2. The mass and stiffness values at each floor have been taken as 1 x 105 kg and 2 x 108 N/m. The present study aims at checking the reliability of RSM towards damage identification under the effect of modeling errors and noise. Based on the study carried out by Umar et al. [1], Young’s modulus (E) and moment of inertia (I), and mass density(D) have been considered as the significant parameters contributing towards the total variance of the model.

3.1 RS Model Generation or the generation of the RS equations, instead of taking Young’s modulus (E) and moment of inertia (I) as significant parameters, stiffness at each floor has been considered as the input parameters. For the purpose of model generation CCD has been considered for which the design bound for stiffness calculations has been fixed at + =2.4 x 108 N/m and – = 1.6 x 108 N/m. The RS model has been generated in MATLAB.

α α

Fig. 2: Simulation Model Considered

3.2 Reliability Analysis of RSM towards Damage Detection In order to check the reliability of the proposed methodology computation of multidimensional probability integrals is required as follows [4,5].

PF= P(g(X)<0) = (11) where, x = {x1 ,x2 ,x3 …. xn}, represents the N-dimensional random variables of the model under consideration; g(x) is the limit state or performance function, such that g(x) < 0, represents the failure domain; and Px(x) is the joint probability density function of the input random variables. Variations that have been considered in the present study are modelling error, variation in the geometric properties, and [202] Relaibility of RSM towards Damage Identification in a Six-Storey Shear Building using ibrationalV Parameters variation in material properties and noise in the modal properties. Noise in the dynamic response has been considered to simulate the actual field conditions. In the present study, RS equations have been generated for the first mode shape and first three modal frequencies. To introduce the modelling error noise has been introduced to the modal properties obtained for each DoEs data sample. This has been done in MATLAB as follows [6],

f =f original (1 + Q1 X randn) (12)

Ф= Фoriginal (1 + Q2 X randn) (13)

Where foriginal is the actual frequency, and f is frequency with random variations. ‘rand’ function in MATLAB

generates random numbers in the range of 0 and 1. The Q1 and Q2 are the percent variations considered in the frequencies and mode shapes [3,6]. They are varied from 0 to 4 percent. The RS equations are generated using these frequencies and mode shapes with random variations. Similarly, to introduce noise same equation as stated earlier is used which is given as follows [3]:

f =f original (1 + Q3 X randn) (14)

Ф= Фoriginal (1 + Q4 X randn) (15)

Where, Q3 and Q4 are the percent variations in the frequencies and mode shapes obtained from the actual model respectively, whose damage is to be calculated. They are again varied from 0 to 4 percentages.

In the present study, these percent variations (Q1, Q2, Q3, Q4) are varied from 0 to 4 percentage and corresponding percentage error in damage detection is computed. More than 5 percentage error in the percentage damage is considered as the failure of the proposed methodology. The corresponding probability of failure is calculated as follow [6]:

Pf = (16)

th Where, xi is i realization of x, NS is the sample size, I[.] is a function that decides whether methodology fails or is safe in state such that I =1, if g(xi ) < 0 otherwise zero [4]. 5 The variation in the Q1, Q2, Q3, and Q4 are random and 10 samples are generated to obtain the percentage damage.

In the present study a 15 percent damage was introduced in the shear model at fourth storey. Corresponding to this Q1, Q2, Q3, and Q4 are varied randomly. A representative damage result is shown in Figure 3. [203] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) A deviation of 5 percent in the damage detection is considered as the failure of the method towards damage detection. The probability of failure obtained is 0.272.

4. CONCLUSION In the present study capability of the RSM towards damage identification in a shear building model has been explored. The paper aims at exploring RSM under the effect of modelling error along with the measurement noise. For these purpose RS equations with modelling error have been generated in MATLAB. These RS models have been generated with different percentage variations in the modelling error. RS equations are then used for damage identifications under the effect of varying noisy data. Reliability analysis is required to be carried out for checking applicability of RSM before implementing it on any structure.

REFERENCES [1] Umar, S., Bakhary, N., Abidin, Z.R.A., Response surface methodology for damage detection using frequency and mode shape, Measurement, 115, 258-268 (2018). [2] Fang, E., S., Perera, R., A response surface methodology based damage identification technique, Smart materials and structures, 18, (2009). [3] Mukhopadhyay, T., Dey, K., T., Chowdhury, R., Chakrabarti, A., Structural Damage Identification Using Response Surface-Based Multi-objective Optimization: A Comparative Study, Arabian Journal for Science and Engineering, 40, 1027–1044 (2015). [4] Ditlevsen, O., Madsen, H., O., Structural Reliability Methods, Chichester, Wiley, 1996. [5] Chowdhury. R, Rao, B.N., Assessment of high dimensional model representation techniques for reliability analysis, Probabilistic Engineering Mechanics, 24, 100–115 (2009). [6] Mukhopadhyay, T., Chowdhury, R., Chakrabarti, A., Reliability analysis of response surface based damage identification method, International Journal of Scientific & Engineering Research, 4, (2013) [7] Myers, H.R., Montgomery, C.D., Anderson-cook, M.C., Response surface methodology: process and product optimization using designed experiments, Wiley, 4, (2015)

[204] Liquefaction Potential Evaluation and Design of Pile-foundation in Liquefiable Soils

M.K. Paradhan1, Shuvodeep Chakrabarty2, G.R. Reddy3 and K. Srinivas4 1Scientist, Homi Bhabha National Institue (HBNI), Mumbai, India 2,3,4Bhabha Atomic Resaerch Centre (BARC), Mumbai, India E-mail: [email protected]

ABSTRACT Foundation system is part of civil engineering structures transfers the super structure loads to suitable and capable soil strata below it. Pile foundation is a category of deep foundation which is more commonly recommended at the site where top layer of soils possess low bearing capacity. The loads considered in design of pile foundations are of dead loads, live loads, seismic loads etc. However, if the pile foundations are located at site consists of cohesion less soils, loosely filled, ground water table is close to surface(saturated), the site may be susceptible to liquefaction. Presence of liquefaction layer of soil tends to catastrophic failure of foundation resulting failure of structure and loss of life and life lines. In this paper, it is presented the general concept and load transferring mechanism of pile foundation considering non- liquefiable and liquefiable soil. In the present paper, it is also studied, important parameters evaluated from soil investigation pertain to liquefaction potential evaluation of soils, methods of evaluation of liquefaction potential of soils, engineering measures to overcome the liquefaction of soils, design philosophy of pile foundation in liquefiable soils and various relevant critical issues. It is also presented through a case study the procedures of evaluation of liquefaction potential of soil and engineering measured adopted to overcome problem. Keywords: Pile Foundation, Liquefiable Soil, Liquefaction Potential of Soil, Buckling Failure

1. INTRODUCTION Foundation system may be of shallow foundation or deep foundation based on the depth of foundation below the existing ground level. Pile foundation is more common types of deep foundation provided for high rise structures, offshore structures and if soil is susceptible to liquefy.

1.1 Load Transferring Mechanism of Pile Foundation Various analytical methods reported in literature to assess the load carrying capacity of pile foundation. The load transfer mechanism of pile to soil in vertical and lateral direction is totally different. It also depends upon the various parameters of soil. The vertical load taking capacity of the pile are contributed by the bearing of the tip/end of the piles and also from the surface of the piles along the length due to the friction between pile surface and surrounding soil. The vertical load bearing capacity of the piles depends upon the types of the soil encounter by the piles along its length of the pile and tip of the pile apart from various other parameters. The soil profile along the depth of pile may be cohesive, cohesion less and layered which contribute friction resistance. The types of soil at the pile tip may be rock also which contribute bearing resistance.

1.1.1 Pile Foundation in Cohesion-less Soil The general, the ultimate vertical load capacity of the pile (Qu) in Kn, in granular soil[1] is given by formulae;

[205] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

(1) where Qu is Ultimate loads carrying capacity, Ap Cross sectional area of pile, D: Depth of pile

1.1.2 Pile Foundation in Cohesive Soil Similarly, the ultimate vertical load capacity of the pile (Qu) in Kn, in cohesive soil[1] is given by formulae; (2)

The piles may have subjected to lateral load such soil load in vault types structure, wave action in offshore area and base shear due to earth quake. Hence lateral load performance of pile foundation is assessments also very critical. The behaviours of laterally loaded pile are assumed to follow the differential equation of beam:

(3) where x is length along pile, EpIp flexural stiffness of pile. Sub grade reaction approach very common method adopted in predicting the bearing capacity and deflection of pile subjected to lateral load. In this the pile is treated as a beam supported by Winkler soil model in which soil medium replaced by series of independent and elastic spring. The stiffness of the spring, kh is expressed as follow; (4) where p is reaction of soil along the pile depth and y is the lateral deflection of pile. Matlock and Reese suggested relationship to determinate pile deflection, bending moment, and shear force and pile reaction. In case of pile foundations subjected to lateral loads, the lateral load taking capacity and deflection of piles along the depth of piles are very complex as it depends upon various parameters of piles (semi rigid), Soil Structure Interaction, deform of soil (partially elastic and partially plastic), restrained conditions of pile top in pile cap etc. For defining a pile whether it will act as short rigid pile or long flexible piles it is essential to calculate the Stiffness factor (T) for a particular combination of pile and soil [1](Ref IS 2911 Part 1). Stiffness factor of pile is calculated as; For granular soil and consolidated clay with varying soil modulus

(5) p= lateral soil reaction per unit length of pile at depth z below ground level; y= lateral pile deflection; and, h= modulus of subgrade reaction for which the recommended values are give, Modulus of subgrade reaction of soil deepens upon the types of soil and its density i.e. Loose, dense. The lateral soil resistance forη preloaded clays with constant soil modulus is modelled per the equation:

Where (6) k1 is Terzaghi’s modulus of sub grade reactions determined from load deflection measurements on a 30 cm square plate and B is the width of the pile (diameter in case of circular piles

[206] Liquefaction Potential Evaluation and Design of Pile-foundation in Liquefiable Soils 1.1.3 Earthquake Load The Indian Standard (IS 1893) [2]categorised foundation soils into rock or hard soil, medium soil and soft soils based on observed standard penetration test (N) value . Base shear (Vb) during earthquake is calculated as (7)

Where Vb is base shesr, Ws is weight of structures and Ah is design horizontal seismic coeficient calculated as

(8)

Where z is zone factor indicates the acredential maxumum ground acceleration during earthquake based on zone. I is importance factor of the structure depends upon thefunctional use of it. R is response reduction factor dpend upon the performance of structure during earthquake. Sa/g is spectral acceleartion coefficient depends upon the type of soils, time period of structure (T) and damping ratio. Time period for a typical RC framed structures is calculated as (9)

Where h is height of building. Thereafter the maximum load transfer to the pile foundation are evaluated as the combination of vertical loads from super structures(V), moment(M) and base shear Vb due to earthquake.

1.2 Liquefaction of Soils Liquefaction is a state of cohesion less soil if loosely filled, fully saturated subject to repeated dynamic loads such as earthquake in which soil lose its shear strength and stiffness. Liquefaction phenomena can be categorised as flow liquefaction and cyclic mobility. Flow liquefaction occurs at site when shear strength of soil mass at static equilibrium is greater than the shear strength of soil at liquefied state i.e. residual strength. Cyclic mobility occurs when static shear stress is greater than the shear strength of liquefied state. Liquefaction of soil occurs when pore water pressure developed inside soil skeleton is equal to total vertical overburden stress so the effective stress as per eqn. 1 tends to zero in Effective stress = Total overburden stress - Pore water pressure (10) It’s devastating effects experienced during various past earthquakes and Kobe, Niigata, Chi-Chi and Kutch (2001) few of them.

2. METHODS OF EVALUATION OF LIQUEFACTION POTENTIAL OF SOIL There are various methods to evaluate the liquefaction potential of soil. However, for evaluation of liquefaction potential of soil various soil parameters are required which are obtained by performing geotechnical investigation.

2.1 Soil Investigation Geotechnical investigation of a site is carried out before construction of any civil engineering structures to evaluate the general suitability of site for intent structure. It is also performed to acquire various soil parameter pertain to foundation design and assessments of liquefaction potential of the site etc. The important soil investigations tests about liquefaction of soil are Standard Penetration Test(SPT), Cone Penetration Test(CPT) and shear wave velocity determination etc. [207] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 2.1.1 Standard Penetration Test (SPT) Standard penetration test(SPT) is very common but most important test performed in geotechnical investigation. It is useful in determination of bearing capacity of soil and frequently used in evaluation of liquefaction potential of soil. SPT is defined as the number of blows required to penetrate standard sampler for 300mm after 150mm initial sheeting blows when a standard weight of 63.5kg falls from a height of 750mm. Various corrections on accounts of overburden, and dilatancy are required based on site condition. Further correction for hammer efficiency, drill rod length, sampler and bore hole diameters are performed to evaluate (N1)60 which is used in evaluation of liquefaction potential of soil.

2.1.2 Cone Penetration Test(CPT) Cone penetration test is a direct sounding test (IS 4968 -Part-3 1976 Reaffirmed 1997) conducted at site to obtain a continuous records of soil characteristics varying with depths. It is used to evaluate various engineering properties of soil also evaluate liquefaction potential at a site.

2.1.3 Shear Wave Velocity Spectral-analysis-of-surface-waves (SASW) testing is a proven, method used to determine the variation of shear-wave velocity (VS)with depth.

2.2 Liquefaction Potential Evaluation Prior to planning of construction of civil engineering structures it is required to evaluate the liquefaction potential of site from safety point of view. Liquefaction potential of soils can be evaluated from observed SPT, CPT or shear wave velocity values [3] [4].

2.2.1 Standard Penetration Test (SPT) Soil is considered susceptible to liquefy if factor of safety evaluated as per eqn.1 is less than unity.

(11)

Cyclical stress ratio (CSR) is evaluated as

(12)

Where amax is peak ground acceleration, g is acceleration due to gravity, rd is stress reduction factor, v total vertical stress and is effective vertical stress. 훔 Stress reduction factor is evaluated from eqn. (13)

(14)

The cyclic stress ratio is corrected for earthquake magnitude(km) stress level (k ) and initial stating shear (kα). 훔 For evaluation of cyclic resistance ratio Normalised standard penetration blow count (N1)60 is evaluated as (15)

(16) [208] Liquefaction Potential Evaluation and Design of Pile-foundation in Liquefiable Soils

(17)

Where (18)

Where Pa is atmospheric pressure

The cyclic resistance ratio of soil is estimated from graph depending upon the (N1)60 value. Liquefaction potential is assessed from corrected standard penetration test (SPT) value from Fig.1.

Fig. 1: Relation between SPT(corrected) for M7.5 Magnitude scaling factor earthquake other than magnitude 7.5 (Seed and Idriss, 1982.) presented in table

Table 1: Magnitude Scaling Factor as Per Seed and Idriss 1982 Magnitude Scaling Factor Earthquake Magnitude Number of Equivalent Cyclic Strength M=M M Uniform Cycle Cyclic Strength M=7.5 8.5 26 0.89 7.5 15 1 6 5-6 1.32 5.25 2-3 1.5

2.2.2 Cone Penetration Test(CPT) Normalised cone tip resistance is calculated as

(19)

Where qc is measured cone tip resistance corrected for thin layer with exponent n value 0.5 for sand and 1 for clay. Liquefaction potential is assessed from corrected cone penetration resistance from Fig. 2.

[209] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 2: Relation between CRR and Cone Penetration Resistance(corrected) for M7.5

2.2.3 Shear Wave Velocity Normalised shear wave velocity Vs1 for clean sand is evaluated using

(20)

Liquefaction potential is assessed from corrected shear wave velocity from Fig. 3.

Fig. 3: Relation between CRR and Shear Wave Velocity Vs1 for M7.5

2.3 Engineering Measures A site of proposed project susceptible to liquefy may not be possible to reject due to project demand or scarcity of land. Hence engineering measures are adopted to overcome the problem. Ground improvements or soil stabilizations are carried out to improve the physical p[properties of soil and also to improve the soil resistance against liquefaction. Otherwise pile foundations are recommended at liquefiable soil area.

2.3.1 Pile Foundation in Liquefiable Soil During past strong earthquake [1964, Niigata(Japan)], [1995, Kobe (Japan)], [1989, Loma Prieta], [2001, Kutch (India)], it was experienced severe failure of several structures supported on pile foundations

[210] Liquefaction Potential Evaluation and Design of Pile-foundation in Liquefiable Soils on accounts of occurrence of liquefaction. Pile foundations located at liquefiable soils in addition to superstructure (vertical) and seismic loads subject to lateral flow during occurrence of liquefaction. The surrounding confinements of soil to pile also lost during liquefaction. Liquefaction of soil alter the pile load bearing capacity. The design consideration of pile foundation in liquefiable soils are different compare to the pile design in non-liquefiable soils.

2.4 Design Philosophy of Pile Foundation in Liquefiable Soils During earthquakes pile foundations are subject to vertical loads from superstructures and lateral/ horizontal loads due to earthquakes. During earthquakes piles are subjected to inertia load on accounts of superstructures and kinematic loads due to differential lateral displacements of pile and surrounding soils. In case of liquefaction of soil additional lateral loads are considered on accounts of lateral flow of liquefied soil layer. Various assumption and philosophies are adopted during design, analysis of pile foundation in liquefiable soils.

2.4.1 JRA When the intermediate soils layer is liquefied, the soil layers above the liquefied zone move resulting lateral flow, resulting in passive pressures on the pile. These additional passive pressures rise the moments at the fixity point and thus the moment capacity of pile must be increased. Japanese code of practice JRA (1996) provide the guidelines and load acting principles on piles during the occurrence of liquefaction of soil [5]. The line diagram of assumption of lateral load on pile during liquefaction is shown in Fig. 4.

Fig. 4: JRA (1996) Code of Practice Shows Idealisation of Seismic Design of Pile in Liquefiable Soil Hence pile deign is required to be checked to sustain the additional lateral passive loads. This can be achieved by the increasing pile main longitudinal reinforcement in the originally adopted section or by increasing the pile section.

2.4.2 Buckling Failure During earthquake and occurrence of liquefaction of soil the intermediate liquefied soils layer loss its stiffness and shear strength as results behave as liquid. Pile loss its confinements of surrounding soils and starts behaving as a free standing slender structure as shown in Figure 5. Pile also changes its point of fixity. In this case the pile foundation design also considered the critical load taking capacity relevant to buckling failure [6,7].

[211] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 5: Buckling Failure Concept of Pile Foundation in Liquefiable Soil The minimum pile diameters required to be adopted based on thickness of the liquefiable layer and to sustain the buckling failure (Bhattacharya and Bolton, 2004) [3].

2.4.3 Loss of Friction In the similar way as described above during earthquake and occurrence of liquefaction, the contribution of pile load carrying capacity due to frictional part also decreased. Hence in design of pile foundation the frictional load bearing part offered by liquefiable soil layer is neglected as presented in Figure 6. Accordingly pile length can the increased considering the same.

Fig. 6: No Frictional Resistance Offered of Intermediate Layer to Pile Foundation in Liquefiable Soil

2.4.4 Change of Natural Period The natural period of the system is evaluated during design of structures and foundation. However due to liquefaction of soil the natural period of the system get changes.

[212] Liquefaction Potential Evaluation and Design of Pile-foundation in Liquefiable Soils 3. A CASE STUDY A typical case is considered for evaluation of liquefaction potential of soil. Soil investigation was performed to obtain various soil parameters and to evaluate the liquefaction potential of soil. Various parameters obtained during soil investigation is presented in table.

Table 2: Soil parameters Observed During Soil Investigation and Factor of Safety Against Liquefaction of Soil Serial Depth Unit Effective Fine CSR (N ) (N ) cs CRR FOS No. (m) Weight Unit Weight Content 1 60 1 60 1 0 0 – – – – – 2 3 18.1 8.29 75 0.210 10 17 0.2582 1.22 3 4.5 18.2 8.39 62 0.210 10 17 0.2296 1.09 4 6 18.5 8.69 49 0.220 8 14.5 0.2195 0.99 5 9 18.6 8.79 45 0.215 9 15.8 0.2032 0.94 6 12 18.7 8.89 41 0.190 10 17 0.195 1.023 Evaluated factor of safety from cyclic stress ratio and cyclic resistance ratio is presented in figure 7.

Fig. 7: CRR, CSR and Factor of Safety Against Liquefaction It is observed from figure 7 in the intermediate layer from depth 5.2m to 10.2m the factor of safety against liquefaction is less than unity. Hence the site is susceptible to liquefy. The shear wave velocity obtained from Cross bore hole test obtained at site is presented in table and figure 8.

Table 3: Shear Wave Velocity Obtained from Cross Bore Hole Tset Depth (m) VP (m/s) VS (m/s) Density, ρ (t/m³) m = VP / VS 1.5 538.0 198.0 1.72 2.72 3.0 558.0 228.0 1.70 2.45 4.5 560.0 221.0 1.70 2.53 6.0 561.0 222.0 1.68 2.53 7.5 568.0 240.0 1.68 2.37 9.0 580.0 247.0 1.70 2.35

Table 3 (Contd.)... [213] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

...Table 3 (Contd.)

Depth (m) VP (m/s) VS (m/s) Density, ρ (t/m³) m = VP / VS 10.5 552.0 223.0 1.74 2.48 12.0 592.0 255.0 1.76 2.32 13.5 602.0 270.0 1.82 2.23 15.0 632.0 299.0 1.82 2.11 16.5 682.0 335.0 1.84 2.04 18.0 635.0 307.0 1.82 2.07 19.5 630.0 300.0 1.82 2.10 21.0 642.0 318.0 1.82 2.02 22.5 678.0 339.0 1.86 2.00 24.0 702.0 355.0 1.86 1.98 25.5 712.0 361.0 1.88 1.97 27.0 715.0 367.0 1.88 1.95 28.5 756.0 383.0 1.90 1.97 30.0 775.0 396.0 1.92 1.96 31.5 778.0 412.0 1.94 1.89 33.0 795.0 420.0 1.96 1.89 34.5 815.0 437.0 1.98 1.86 36.0 833.0 448.0 1.98 1.86 37.5 855.0 462.0 2.00 1.85 39.0 876.0 478.0 2.00 1.83 40.5 944.0 515.0 2.10 1.83 42.0 968.0 528.0 2.20 1.83

Fig. 8: Variation of Shear Pwave and Swave Velocity with Depth Semi empirical method recommended by Idriss and Boulanger (2004) [4] is adopted to evaluating the liquefaction potential of soils. It is observed the factor of safety against Liquefaction is less than unity for an intermediate layer from 5.20m to 10.200m depth. Hence the pile must be designed neglecting the frictional contribution offered by intermediate liquefied surrounding soil.

[214] Liquefaction Potential Evaluation and Design of Pile-foundation in Liquefiable Soils Pile is designed considering the vertical superstructure load, moment and base shear generated due to seismic. Pile is constructed as per guidelines of IS 2911 [8]. Pile is recommended as RCC cast in-situ of length and diameter as presented in table.

Table 4: Approximate Size of Bored Cast in-situ RCC Piles Safe Vertical Capacity of Pile Lateral Capacity Pile Dia. Cut-off Level Pile Tip Level In Compression In Tension Uplift(Ton) (ton) (Ton) 600mm 100 70 3.1 1.50 m below 27.0 m below 750mm 140 100 3.8 E.G.L. E.G.L. 1000 mm 245 160 5.2 Suitable methods of ground improvements techniques can be adopted to mitigate the liquefaction potential of soil.

4. RESULTS AND DISCUSSION An efficient, safe and effective design of the pile foundations to resist the estimated earthquake loads is a major concerned issue with the increasing seismic activities in the recent times. In this interest a study is carried out the various critical issues considered during design of a suitable and efficient pile foundation. Various methods of evaluation of liquefaction potential of soil also presented. A typical case study is also presented for evaluating the liquefaction potential and design recommendation is briefed for a liquefiable soil.

ACKNOWLEDGMENT The academic and research support provided by institution, Homi Bhabha National Institute(HBNI) and Bhabha Atomic Research Centre(BARC) is gratefully acknowledged by the authors.

REFERENCES [1] BIS. IS: 2911 (Part 4) - 1985 (Reaffirmed 2010) Code of practice for design and construction of pile Foundation Part 4 Load test on piles 1985. [2] IS 1893 (2002), Criteria for earthquake resistant design of structures, BIS, New Delhi, India [3] Youd TL, et al. “Liquefaction resistance of soils: Summary report from the 1996 NCEER/NSF workshops on evaluation of liquefaction resistance of soils,” Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 127, 10, 817-833, 2001. [4] Idriss, I.M. and Boulanger, R.W. (2004), “Semi-Empirical Procedures for evaluating Liquefaction Potential during Earthquakes”, Proc. 11th International Conference on Soil Dynamics & Earthquake Engineering, January 7-9, 2004, Berkeley, California, USA [5] JRA(1996) japanees road association, specification for highway bridge, [6] Bhattacharya, S and Madabhushi, S.P.G. (2008), A critical review of the methods for pile design in seismically liquefiable soils, Bulletin of Earthquake Engineering, 6, 407-446. [7] Bhattacharya, S and Bolton, M. (2004) Buckling of piles during earthquake liquefaction, Proc. 13th World conference on Earthquake Engineering, August 1-4, 2004, Vancouver, Canada, Paper No. 95. [8] IS 2911 (1979), Code of practice for design and construction of pile foundations, BIS, New Delhi, India.

[215] Effect of Sorption Phenomena in Groundwater Solute Transport Modeling

Pappu Kumar1 and Anshuman Singh2 1Research Scholar, Department of Civil Engineering National Institute of Technology, Patna, Bihar, India 2Associate Professor, Department of Civil Engineering National Institute of Technology, Patna, Bihar, India E-mail: [email protected]

ABSTRACT In this paper solution of advection-dispersion with different sorption, the equation is used for the prediction of solute concentration in groundwater. due to increasing the groundwater pollution the effect of different chemical transport plotted. The fate and sorption process of different chemical different degradation constant. We used the analytical solution to evaluate the transport phenomenon and analysis of the chemical dissolved in groundwater. The solute transport model simulated with the analytical solution and final result obtained using MATLAB software. The solution of a test problem based on the sequential degradation of the different chemical in the groundwater. Keyword: Groundwater, Advection, Dispersion, Sorption, MATLAB Software

1. INTRODUCTION Distribution of Contaminant affects the sorption process, the advection-dispersion of groundwater modeling equation involves chemical and hydraulics parameter. The sorbing chemical equation uses the evaluation of such parameters at every point in the groundwater. In this steady one-dimensional groundwater sorption model developed, migration of contaminants through groundwater. In this study, many assumptions are taking. Now a day groundwater contamination due to landfill, according to the European Environment Agency, about 2.5 million affected[1]. The characterization of solute dispersion plays the most central risk assessment adopted many national environmental agencies. Quantitative solute understanding of kinetics and sorption mechanisms heavy metal adsorption-desorption and transport processes, contaminant flow through the groundwater can be represented by advection-dispersion diffusion equation[2]. the saturated flow the soil is saturated, homogeneous and hydrodynamics.

2. PURPOSE AND SCOPE This paper describes the groundwater sorption and transport model. The analytical solution of the advection-dispersion of the chemical diffusion, the solution of one dimensional given by [3]. all the solution is used as many assumptions, all solutions are given in the analytical solution and used as MATLAB Script and plot between distance and concertation. Advection is the process that can be solute transported by the velocity of subsurface water. The fluid particle moves along the intensity of fluid-particle flow. the average intestinal fluid velocity represents advection-dispersion mathematical equation. it is also describing the mixing of solute particle. The groundwater flowing water moves with average velocity.

[216] Effect of Sorption Phenomena in Groundwater Solute Transport Modeling 3. MATHEMATICAL FORMULATION The general equation of transport equation [4, 5], ∂cρ ∂ c ∂∂ cc +b =D −− vCλ (1) ∂tθ ∂ x22x ∂∂ xx

4. MODEL INITIAL AND BOUNDARY CONDITIONS The partial differential equation for groundwater solute transport modeling with sorption term. This equation can be analytically solved by initial and boundary condition. Initial and boundary condition complete the model of groundwater. The dependent variable in the given advection-dispersion equation sorbed concentration is variable in this topic the simple analytical solution to our model. We will keep the initial and boundary conditions simple. Complex initial and boundary.

4.1 Initial Conditions C=∂== M( xs ), 0, t 0, (2) −∞ ≤x ≤ ∞

4.2 Boundary Conditions ∂C = 0, ∂x (3) x → ±∞

5. ANALYTICAL SOLUTION M c ( xs, ) = erx (4) v− Drx

The solute transport model is based on an earlier solution given by [6, 7];

Parameter Value Porosity 0.25 Bulk density 1.5 g/cm3 Dispersion coefficient 0.1 cm2/d Pore velocity 1 Degradation rate constant 0.03 d−1 First order mass transfer rate constant 0.1 d−1

Sorption distribution coefficient kd 3 Groundwater contaminant flow through subsurface with the groundwater velocity.

6. RESULT In this paper, the degradation effect can be plotted between concentration and distance. The result determines the concentration any distance and degradation rate are taken for different condition and compare the concentration distribution. First, a set of heterogeneous and contaminated synthetic aquifers is generated; second, the spreading of a solute plume subject to the first-order degradation is simulated. [217] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 1: Caparison of the Benzene Sorption Value Minimum (λ = 0.05) with the Maximum λ = 3

Fig. 2: Caparison of the Perchloroethylene (PCE) Sorption Value Minimum (λ = 0.07) with the Maximum λ = 1.2

Fig. 3: Caparison of the Trichloroethylene (TCE) Sorption Value Minimum (λ= 0.05) with the Maximum λ = 4.75 [218] Effect of Sorption Phenomena in Groundwater Solute Transport Modeling This comparison is conducted for different degrees of heterogeneity, represented by lognormally distributed random conductivity fields. The results indicate that, with increasing degree of heterogeneity, ‘‘measured’’ degradation rate constants become uncertain with a high variability around the true constant. Measured rate constants tend to overestimate the true constant by up to one order of magnitude.

7. CONCLUSION In this analysis the analytical solution used for ADE with variable of sorption parameter, we used benzene of the sorption value ( = 0.05 to = 3 the minimum and maximum value shows that concentration of benzene transportation more at minimum value and less at minimum value of sorption same as perchloroethylene (PCE)λ ( = 0.07 λto = 1.2) and Trichloroethylene (TCE) ( = 0.05 to = 4.75). This study considered the sorption value is an important parameter in the groundwater solute transport model. λ λ λ λ REFERENCES [1] T.U. Söderberg et al., “Metal solubility and transport at a contaminated landfill site–From the source zone into the groundwater,” Science of the Total Environment, vol. 668, pp. 1064-1076, 2019. [2] W. McNab Jr and T. Narasimhan, “A multiple species transport model with sequential decay chain interactions in heterogeneous subsurface environments,” Water resources research, vol. 29, no. 8, pp. 2737–2746, 1993. [3] M.N. Goltz and M.E. Oxley, “Analytical modeling of aquifer decontamination by pumping when transport is affected by rate-limited sorption,” Water Resources Research, vol. 27, no. 4, pp. 547-556, 1991. [4] L.W. Gelhar and C.L. Axness, “Three-dimensional stochastic analysis of macrodispersion in aquifers,” Water Resources Research, vol. 19, no. 1, pp. 161-180, 1983. [5] M.L. Brusseau, “Soil and groundwater remediation,” in Environmental and Pollution Science: Elsevier, 2019, pp. 329-354. [6] C. Yang, J. Samper, and L. Montenegro, “A coupled non-isothermal reactive transport model for long-term geochemical evolution of a HLW repository in clay,” Environmental Geology, vol. 53, no. 8, pp. 1627-1638, 2008. [7] M.N. Goltz and P.V. Roberts, “Three-dimensional solutions for solute transport in an infinite medium with mobile and immobile zones,” Water Resources Research, vol. 22, no. 7, pp. 1139–1148, 1986.

[219] Effect of Soaking Period of Soil on Liquid Limit and Plastic Limit

Saurav Shekhar Kar1, Suraj Kumar2, Anurag Singh3 and L.B. Roy4 1Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2,3B.Tech 6th Semester Students, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 4Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected]

ABSTRACT The present study compares liquid limit and plasticlimit values obtained by the effect of soaking the soil for 24 hr. The liquid limit and plastic limit values are determined for soil samples collected from five different locations of Patna Bihar. It is the most vital geotechnical properties used for fine-grained soil especially cohesive soil. The liquid limit and plastic limit of five different soil are varied between 0.24% to 11.64% and 24.36% to 53.30% respectively. It is observed that the value of liquid limit and plastic limit obtained after the 24 hr kneading is more than the values obtained just after kneading with the maximum difference of liquid limit and plastic limit are 4.64% and 6.55% respectively and minimum difference of liquid limit and plastic limit are 0.12 % and 3% respectively. The liquid limit test was done using Casagrande’s liquid limit apparatus and plastic limit test by using hand method.

1. INTRODUCTION Atterberg in 1911 has described seven limits that control the behavior of cohesive soils at varying moisture contents. Out of seven limits only the liquid limit, plastic limit and shrinkage limit are commonly use. This is because it determines the range of plastic behavior of the soil very accurately and easily. The Atterberg limits are perhaps the oldest and most widely used of all the soil properties. Despite their widespread use in soil-engineering practice for identification and classification of soils, the liquid and plastic limits have received relatively lesser attention from research workers in the past. Originally, the Atterberg limits were devised for purpose of classification or in particular to knowing the plastic nature of the cohesive soils or both. However in the recent past, they have been correlated to various properties like surface area, geological and mineralogical history, cation exchange capacity, swelling behavior,shear strength, california bearing ratio, compaction characteristics, and so forth. Further, these correlations have been used to check new data or to predict soil behavior for design work.

1.1 Liquid Limit Atterbergfirst proposed the liquid limit test in 1911 and improved by Casagrande (1932–1958), is the commonly used soil test. As per Giovanni Spagnoli (2012), the liquid limit is defined as the moisture content at which a soil is practically in liquid state, i.e., soil changes from plastic state to liquid state. If the amount of water content increases, the spacing between the particles increases which leads to decrease in interaction between the soilparticles ultimately affecting the mechanical behavior. This is the stage when soil changes from having infinitesimal shear strength to possessing no shear strength.As per Sowers et al. (1960), the liquid limit test is actually a determination of the shear strength of a soil.

1.2 Plastic Limit Atterbergin 1911 was first to described the plastic limit of soils. It is defined as the water content at which soil just begins to crumble when rolled into a thread around 3 mm diameter. The plastic limit test is also [220] Effect of Soaking Period of Soil on Liquid Limit and Plastic Limit known as thread-rolling test. This test was standardized at the US Public Roads Bureau in the 1920s and 1930s, and has become as one of the standard soil tests. In plastic state, the soil can be rolled into various shapes without rupturing it, due to its plasticity. It is observed that the brittle failure in plastic limit test is occurred either by air entry or by the cavitation. The fallacy that strength at plastic limit is a constant is highlighted, and the implications for geotechnical practice are discussed.

2. MATERIALS AND METHOD The liquid limit and plastic limit for five different soil samples are collected from following locations at Patna (INDIA) 1. BY-PASSS: Soil was collected from a construction site, whose initial earth work was in progress. 2. JAGANPURA: Soil was collected from a rural land from depth of 20-30 cm. 3. BEUR: Soil was collected from a construction site of a mall, whose initial earth work was going on. Soil was collected from a depth of 40cm to 50cm. 4. MITHAPUR: Soil was collected from a ground beside mithapur bus stand on which heavy construction was going on. Soil was collected at a depth of 150cm to 180cm 5. NIT-PATNA: Soil was collected from a barren land at depth of 20-30 cm

Site Longitude Latitude By-pass 85.156980 N 25.582725 E Jaganpura 85.148569 N 25.580568 E Beur 85.0988294 N 25.5777811 E Mithapur 85.1320764 N 25.5875397 E Nit Patna 85.170979 N 25.621199 E

2.1 Determination of Atterberg Limit Atterberg in 1911 examined the consistency of soil. Consistency is described as the degree of softness of a soil in a qualitative term. Atterberg, conducted various tests for determining the properties of fine-grained soils especially clay soils. He observed that if the amount of water in a clay mixture is gradually decreased, the clay mixture experience a change from liquid state toplastic state and lastly into solid state. He noticed that the soil sample passes through four different state of consistencywith the decrease in the moisture content. The four different stateused to represent the consistency of a clay are the liquid state, the plastic state, the semi-solid state, and the solid state. The moisture content corresponding to the boundary of one state to other state is known as Atterberg Limits. The testing procedure of Atterberg’s was subsequently improved by A.Casagrande.Atterberg limit and consistency indices are used for classification of fine grained soil especially cohesive soil.

2.1.1 Casagrande’s Liquid Limit Device The liquid limit of a soil sample is determined with liquid limit device designed by A. Casagrande, which is also known as Casagrande’s liquid limit apparatus. The apparatus consist ofbrass cup which is raised by 1 cm and made to fall on a rubber compound base by operating the handleattached to it. The height of fall of the cup can be adjusted with the help of an adjusting screw. The liquid limits are determined for the soil which is finer than a 425µ. About 120 g of air-dried soil sample is uniformly mixed with water to make soil paste. A portion of soil paste is placed on the brass cup and is levelled to have maximum depth of 10 mm. With the help of grooving tool, a groove having the dimension of 11 mm wide and 8 mm depth is cut in the soil placed in the cup. The grooving tool should always be held perpendicular to the [221] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) cup at the point of contact. The handle is revolved at a rate of 2 revolutions per second and the number of blows required to close the groove is noted. This test is repeated by varying the moisture content of the soil sample. A minimum of four tests should be carried out by altering the moisture content of soil sample such that the number of blows required to close the groove should lie within the range of 10 to 40. A graph between moisture content in x-axis and number of blows (log 10) in y-axis is plotted and the equation of water content is given by:

Where, w = water content

If = slope of flow curve N = number of blows C = constant The forces that resist the sliding of the sides of the groove are the shear resistance of the soil. The water content corresponding to 25 number of blows required to close the groove is called as the liquid limit. The number of blows for a specified length is indirectly a relative measure of the shearing resistance of the soil at the corresponding water content. It is worth to mention that plastic soil at liquid limit possess a constant value of shearing resistance.

2.1.2 Plastic Limit Test The plastic limit test is also known as thread test or rolling test. About 15g of air-dried soil finer than 425µ, is mixed uniformly with sufficient amount of water. The soil is rolled on a glass plate with the palm of hands, until it is about 3mm in diameter. The whole process of mixing and rolling is repeated till the soil shows the sign off crumbling when the diameter is 3mm. The water content of the crumbled portion of the thread is determined. This is called plastic limit.

2.2 Discussion on Atterberg’s Limits The Atterberg’s limit i.e., liquid limit and plastic limit are major factors which give guidance to a person to easily understand the consistency of soil and its plasticity especially for clay soil. For a clay soil, at liquid limit the shear strength is constant but varies at plastic limit. With increase in the plasticity of soil, the shearing strength also increases. The soil having high plasticity e.g. fat clay will have higher shearing strength at plastic limit.

3. RESULTS AND DISSCUTION The summary of the results are as given in tables

3.1 By Pass, Patna, Bihar

Table 1 DAY 1 DAY 2 Sr. No. No. of Blows Water Content (%) No. of Blows Water Content (%) 1 15 51.85 17 54.3 2 28 47.22 20 51.9 3 40 46.33 27 47

[222] Effect of Soaking Period of Soil on Liquid Limit and Plastic Limit

FLOWFlow CurveCURVE 55 54 53 52 51 50 49 DAY 1 48 DAY 2 Water Water content (%) 47 46

Water Content (%) Water 45 10 100 No.No. of blows of blows

Graph 1: Flow Curve of Sample Collected from By-Pass, Patna

3.2 Jaganpura, Patna

Table 2 DAY 1 DAY 2 Sr. No. No. of Blows Water Content (%) No. of Blows Water Content (%) 1 11 42.62 17 42.85 2 19 37.93 25 38.55 3 31 32.84 36 35.52

FLOWFlow CurveCURVE

44 42 40 38 36 DAY 1 34 DAY 2 Water Water content (%) 32

Water Content (%) Water 30 10 100 No.No. of blows of blows

Graph 2: Flow Curve of Sample Collected from Jaganpura, Patna

3.3 Beur, Patna

Table 3 DAY 1 DAY 2 Sr. No. No. of Blows Water Content (%) No. of Blows Water Content (%) 1 18 50.14 25 50 2 24 46 39 48.9 3 29 42.81 60 48

[223] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

FlowFLOW Curve CURVE

54 52 50 48 46 DAY 1 44 DAY 2 Water Water content (%) 42

Water Content (%) Water 40 10 100 No.No. of of blows blows

Graph 3: Flow Curve of Sample Collected from Beur, Patna

3.4 Mithapur, Patna

Table 4 DAY 1 DAY 2 Sr. No. No. of Blows Water Content (%) No. of Blows Water Content (%) 1 16 60 15 63.1 2 23 58.1 17 62.36 3 28 56.92 29 55.88

FLOWFlow Curve CURVE

64 62 60 58 56 DAY 1 54 DAY 2 Water Water content (%) 52

Water Content (%) Water 50 10 100 No.No. of blowsof blows

Graph 4: Flow Curve of Sample Collected from Mithapur, Patna

3.5 Nit Patna

Table 5 DAY 1 DAY 2 Sr. No. No. of Blows Water Content (%) No. of Blows Water Content (%) 1 15 32.78 13 35.15 2 22 26.14 24 28.45 3 32 21.5 28 24.36

[224] Effect of Soaking Period of Soil on Liquid Limit and Plastic Limit

FLOWFlow CurveCURVE 40 38 36 34 32 30 28 DAY 1 26 DAY 2 Water Water content (%) 24 Water content (%) Water 22 20 10 100 No.No. of blowsof blows Graph 5: Flow Curve of Sample Collected from NIT-Patna

4. RESULTS AND DISCUSSION The summary of the test results are as given in the table

Table 6: Comparison of Liquid Limits Sample Liquid Limit Just After Kneading Liquid Limit After 24 Hours By-Pass 48.28 48.40 Beur 34.53 38.55 Mithapur 45.36 50.00 Jaganpura 57.63 58.04 Nit-Patna 24.75 27.43

Table 7: Comparison of Plastic Limits Sample Liquid Limit Just After Kneading Liquid Limit After 24 Hours By-Pass 17.51 23.99 Beur 12.29 18.84 Mithapur 22.86 28.43 Jaganpura 14.08 18.52 Nit-Patna 9.02 12.02

5. CONCLUSION 1. The value of liquid limit of the soil sample increases after the soaking period of 24 hourshaving minimum and maximum difference of 0.12 % and 4.64 % respectively. 2. The value of plastic limit of the soil sample increases after the soaking period of 24 hourshaving minimum and maximum difference of 3 % and 6.55 % respectively. 3. Increase in liquid limit of five different soil sample varied between 0.24% to 11.64 %. 4. Increase in plastic limit of five different soil samplevaried between 24.36% to 53.30%.

[225] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) REFERENCES [1] Text book of Soil Mechanics and Foundation Engineering by V.N.S. Murthy. [2] S.K. Haigh, P.J. Vardanega and M.D. Bolten 2013. “The plastic limit of clay” journal of geotechnique 63, No. 6, pp. 435-440. [3] Zahra Zolfaberg, Mohamamd Reza Mosaddeghi, shamsollahAyoubi and Hamid kelishadi 2015.“soil atterberg limits and consistency indices as influencedby land use and slope position in western Iran”J.Mt.sci(2015)12(6);1471-1483. [4] https://www.britannica.com/science/clay-mineral/chemical-and-physical-properties [5] Abdelaziz El-Shinawi, march 2017 “A Comparison of Liquid Limit Values for Fine Soils: A Case Study at the North Cairo- Suez District, Egypt” Journal Geological Society of India Vol. 89, March 2017, pp. 339-343.

[226] Performance Evaluation of Reclaimed Asphalt Pavement (RAP) as Aggregates when Used with Waste Cooking Oil as a Rejuvenator in Bituminous Pavements

Durgesh Sonawane1 and Pravin Chaudhari2 1Post Graduate Student, M.Tech. Construction Management, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Assistant Professor, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected]

ABSTRACT This paper shows that when the RAP is replaced with virgin aggregates in the mix to reduce the cost of virgin aggregate and to minimize use of bitumen by addition of rejuvenating waste cooking oil for surface layer of road. The RAP is used to replace virgin aggregate in the proportion 30%, 40% and 50%. The bitumen which is to be used is also rejuvenated with waste cooking oil to improve the viscosity of mix and decreases the cost of mix. The percentages of bitumen replaced is 1, 2 and 3%. These results were compared with virgin bitumen of 60/70 grade. Marshall tests was performed for Marshall stability, air voids percent, bulk specific gravity, void filled with bitumen, Marshall flow and for optimum binder content. Various tests of aggregates replaced with RAP is performed and tests on bitumen rejuvenated with oil are also carried out. The study focuses on obtaining the optimum values of RAP replacement and oil replacement. Keywords: RAP, Marshall Stability, Waste Cooking Oil, Waste Materials

1. INTRODUCTION

1.1 General Reclaimed asphalt pavement (RAP) it is the newest construction technique which is used for the road construction with bitumen. RAP material can be easily available where renovation or reconstruction of road is being carried out. The rejuvenated waste cooking oil also available in large quantity at cheap cost. By using of this RAP and waste cooking oil the cost of the project may come out to be less.

1.2 Production of RAP Materials RAP can be obtained by crushing the material obtained from demolished road. RAP consist of aggregate and binder material bound together. Properties of RAP-A comparison is carried out between RAP and crushed natural aggregates. RAP incorporates a very high content of fines that is resulted from degradation of material overall operations of milling and crushing. Typical properties of RAP shown in below:

Table 1: Interview Format for Factors Decision Sr. No. Parameters Values 1 Unit Weight (Kg/m3) 1900–2250 2 Moisture Content Max. 3–5%

Table 1 (Contd.)... [227] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

...Table 1 (Contd.)

Sr. No. Parameters Values 3 Asphalt Content 5–6% 4 Asphalt Penetration (%) at 250C 10–80 5 Compacted Unit Weight (Kg/m3) 1500–1950 6 California Bearing Ratio (CBR) 100% RAP: 20–25% Required consumption of natural mix which can be reduced by the using of RAP materials. By using of rejuvenate waste cooking oil the quantity of bitumen which also can be reduce. The study shows that the replacement of RAP which is 30, 40, 50% with as compared with standard specification, 40% of RAP shows better result with 2% of rejuvenated waste cooking oil. With this proportion produce a strong and better pavement. Some benefits of RAP is as follows: ●● Lower price. ●● Reduce consumption and use natural resources. ●● Reduction of damages to the other roads due to the transports of materials from sites of quarry. ●● No increase within the thickness of pavement, that is significant for urban roads developed and highways. ●● As the transportation is reduced leading for energy saves i.e. less consumption of fuel. Recycle of processed bituminous material has gained a lot of popularity in India in recent times because of several successful trials within the designated projects. An in depth investigation of laboratory is needed so as to use RAP in HMA in conjunction with Cold asphalt mix (CAM) to confirm that mixture have a necessary minimum strength and also the sturdiness. For higher performance the subsequent points should even be thought about that are unit listed below: ●● Quality management and extra process. ●● Classifying RAP. ●● Changing virgin binder grade. ●● Preparation of the materials for mix design. ●● Blending of virgin in conjunction with RAP binders. ●● Assessment of performance. ●● Sources of RAP. The various possible sources of RAP are as follows: ●● Generation for milling for layer of hot mix asphalt. ●● Full depth removal pavement. ●● Waste generated from HMA at a plant. ●● Milling is a process of removal and scraping of distressed upper layer of the existing pavement to the specified depth. ●● This process is inclusive of grinding by machinery and filling of RAP into a vehicle for transport. Amount of binder also can be reduced in asphalt paving mixes by taking RAP materials. The pavement performance by consumption is to 30 % RAP material is similar to that of the pavement made with aggregates which are natural with no RAP materials. Increase demand of aggregates and binder provide may be meeting out up to certain extent by taking reclaimed asphalt [228] Performance Evaluation of Reclaimed Asphalt Pavement (RAP) as Aggregates when Used with Waste Cooking Oil as a Rejuvenator in Bituminous Pavements pavement (RAP) materials in hot mix asphalt (HMA) and alternative courses of the flexible pavements like sub-base and base. Usage asphalt creates a cycle of recycle that optimizes the utilization of natural resources and sustains the asphalt business. Economy, ecology conservation is all achieved once the 2 main elements i.e. asphalt and aggregate is reused as construction materials to produce a strong and improved pavement. There is a need of rehabilitation and construction of roads in rural areas in cost effective way. Road construction is growing at a very fast rate also the quality of existing roads are deteriorated and their rehabilitation work is difficult budget for the government. ●● To select the best proportion of RAP with waste cooking oil to give best results. ●● To use the above proportion in rural areas in cost effective way. ●● In past years, interest of the recycling of industrial by products and has increased. ●● Studies of bitumen mix to the reclaimed (Recycled) asphalt pavement, rejuvenated with waste cooking oil.

2. MATERIALS AND METHODS Source of RAP Collection: The RAP which required for replacement of virgin aggregate which were collected from Mumbai CST link road. The ongoing work of Mumbai metro is the reason for redevelopment of that part of the road. There Reclaimed Asphalt is considered waste. RAP used in this research is collected from that region. Variability of RAP: In this study the gradation of RAP which required will be tested in laboratory with the replacement of aggregate with RAP material and test which carried out with aggregate that are aggregate impact value, Los Angeles Abrasion Value, Aggregate Crushing Value.

Table 2: Physical Properties of RAP Materials Property Value Unit weight 21.5kN/m3 Moisture content 5% Asphalt content 3.8% Asphalt penetration 38 to 25c Absolute viscosity 19000 poise at 60c Compacted unit weight 19kn/m3 California bearing ratio 26% for 100% RAP

Rejuvenated Waste Cooking Oil with Bitumen: The study in which the bitumen which added with waste cooking with various percentage to minimize quantity of bitumen. For that testing on bitumen which carried out to find out best percentage of waste cooking oil. Test which carried out are, ductility, penetration, softening point, viscosity.

Table 3: Properties of Bitumen as Per IS 73:2006 Sr. No. Properties Requirements As Per IS 73:2006 1 Penetration (1/10mm) 50–70 2 Ductility (cm) 75 Min 3 Softening Point (OC) ≥ 47 4 Viscosity (Pas) At(600C) ≤ 3 Pas 5 Viscosity (Pas) At(1350C) ≤ 3 Pas

[229] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.1 Marshall Mix Design

Table 4: Specification of Aggregate Required as Per IRC 94. For Grade 1 and Grade 2 Aggregate Sieve Size Grading 1 (% Passing) Grading 2 (% Passing) 37.5 mm - 100 26.5 mm 100 85–100 19.0 mm 85–100 71–95 Table 5 The mix design as per IRC 94 for marshall 13.2 mm 63–82 58–82

9.5 mm 52–74 52–72 Sr. No. Criteria Spec. Limit 4.75 mm 39–54 35–50 1 No. of compaction blow on each end of Marshall specimen 50 Table2.36 mm 5 The mix design as per IRC 94 for marshall28–43 28–43 2 Marshall 600 stability µm in Kg. (minimum) 15–27 340 15–27 3 Marshall300 flow µm inSr. mm No. Criteria 7–21 2 – 4 Spec. Limit7–21 4 Per cent 150voids µm in mix1 No. of compaction blow on each5–15 end of Marshall5 – 10 specimen 50 5–15 5 Per cent 75voids µm in mineral2 Marshall aggregate stability filled with in Kg. bitumen (minimum)2 –8 55 – 75 340 2–8

6 Binder content per3 cent byMarshall weight flowof total in Tablemmmix 5: The Mix Design4.5 as – Per 6.0 IRC 94 for Marshall2 – 4 Sr. 4No. Per cent voids in mix Criteria 5 – 10 Spec. Limit 15 Per centNo. voids of compaction in mineral aggregateblow on each filled end with of bitumenMarshall specimen 55 – 75 50 In Marshall Mix design, various sizes aggregates of sieves were taken according as mentioned in IRC 94. Binder 26 BinderMarshall content perstability cent byin Kg.weight (minimum) of total mix 4.5 – 6.0 340 content of 4% to 6% was taken in the Marshall Mix design with 0.5% bitumen content increment in each test. 3 Marshall flow in mm 2–4 4000gm of aggregates and filler material4 is heatedPer at cent a te voidsmperature in mix of 175°C. The heated aggregates and bitumen 5–10 are completely mixed atIn a Marshalltemperature5 Mix of design, 175°C.Per various Thecent mivoids sizesxture inaggregates mineralis placed aggregate ofin sievan esalready filledwere with takenpreheated bitumen according mould as and mentioned is in IRC55–75 94. Binder compacted by a 75 blowscontent of Ram of on 64% each to side.6% was TheBinder taken mix content wasin the kept per Marshall undisturbed cent by Mix weight forde signof24 totalhours with mix and0.5% then bitumen Marshall content test increment4.5–6.0 in each test. was done in lab. This isIn 4000gmhelpful Marshall toof findaggregates Mix out design, stability and filler variousand materialflow sizesof sample.is heatedaggregates With at a tereplacementmperature of sieves ofof were 175°C.RAP taken with The various heatedaccording aggregates as mentioned and bitumen in IRC 94. percentage of 30, 40, 50%.Binderare completely content mixed of 4% at ato temperature 6% was takenof 175°C. in the The Marshall mixture is Mix placed design in an with already 0.5% preheated bitumen mould content and is increment in each test. 4000gm of aggregates and filler material is heated at a temperature of 175°C. The heated compacted by a 75 blows of Ram on each side. The mix was kept undisturbed for 24 hours and then Marshall test Specific Gravity of the aggregatesmix Gt and bitumen are completely mixed at a temperature of 175°C. The mixture is placed in an alreadywas done preheatedin lab. This ismould helpful and to find is outcompacted stability a ndby flow a 75of sample.blows Withof Ram replacement on each of RAPside. with The various mix was kept specific gravity Gt is the undisturbedspecificpercentage gravity of 30, for without 40, 24 50%. hours considering and airthen voids, Marshall and is given test by:was done in lab. This is helpful to find out stability and flow of sample. With replacement of RAP with various percentage of 30, 40, 50%. 1 + 2 + 3 + Specific Gravity of the mix Gt (1) = SpecificM1 M2 G1 M3Gravity Mb of the Mix Gt + + + ܹ ܹ ܹ ܹܾ G2 G3 Gb :ݐ specificspecific gravity gravity G t Gis the is thespecific specific gravity gravity without without considering considering air voids, and air is voids, given by: and is given byܩ t 1 + 2 + 3 + (1) (1) Here, W1 is the weight of coarse aggregate in the = M1 total M2mix, G1 W2M3 is Mbthe weight of fine aggregate in the total mix, W3 + + + ܹ ܹ ܹ ܹܾ G2 G3 Gb ݐ the weight of bitumen in the total mix, G1 is the apparent specificܩis the weight of filler in the total mix, Wb is gravity of coarse aggregate,Here, G2 W1 is theis the apparent weight specific of coarse gravity aggregate of fine aggregate, in the total G3 ismix, the W2apparent is the specific weight of fine aggregate in the total mix, W3 is the weight of filler in the total mix, Wb is the weight of bitumen in the total mix, G1 is the gravity of filler and Gb isHere, the apparent W1 is the specific weight gravity of coarse of bitumenaggregate in the total mix, W2 is the weight of fine aggregate in the total mix, W3 apparent specific gravity of coarse aggregate, G2 is the apparent specific gravity of fine aggregate, G3 is is the weight of filler in the total mix, Wb is the weight of bitumen in the total mix, G1 is the apparent specific Bulk Specific Gravity ofthe mix apparent Gm specific gravity of filler and Gb is the apparent specific gravity of bitumen. gravity of coarse aggregate, G2 is the apparent specific gravity of fine aggregate, G3 is the apparent specific Bulk Specific Gravity of Mix Gm The bulk specific gravitygravity or the ofactual filler specific and Gb gravityis the apparent of the mix specific Gm isgravity the specific of bitumen gravity considering air voids The bulk specific gravity or the actual specific gravity of the mix Gm is the specific gravity considering air and is found out by: voidsBulk Specific and is Gravityfound out of mix by: Gm (2)

The =bulk specific gravity or the actual specific gravity of the mix Gm is the specific gravity considering air voids − (2) ܹ݉ ܩ݉and is found out by: ܹ݉ [230] ݓܹ (2)

= . Where, Wm is the weight of mix in air, Ww is the weight of mix − in water. ܹ݉ ܩ݉ ܹ݉ Air Void percent Vv ݓܹ

Air voids Vv is the percent. Where, of air voidsWm is by the volume weight in of the mix specimen in air, Ww and is is the given weight by: of mix in water.

Air Void( − percent )100 V v (3)

݉ܩ ݐܩ :ݒAir voids Vv is the percent of air voids by volume in the specimen and is given byܸ ݐܩ ( − )100 (3)

݉ܩ ݐܩ ݒܸ ݐܩ Table 5 The mix design as per IRC 94 for marshall

Sr. No. Criteria Spec. Limit 1 No. of compaction blow on each end of Marshall specimen 50 2 Marshall stability in Kg. (minimum) 340 3 Marshall flow in mm 2 – 4 4 Per cent voids in mix 5 – 10 5 Per cent voids in mineral aggregate filled with bitumen 55 – 75 6 Binder content per cent by weight of total mix 4.5 – 6.0

In Marshall Mix design, various sizes aggregates of sieves were taken according as mentioned in IRC 94. Binder content of 4% to 6% was taken in the Marshall Mix design with 0.5% bitumen content increment in each test. 4000gm of aggregates and filler material is heated at a temperature of 175°C. The heated aggregates and bitumen are completely mixed at a temperature of 175°C. The mixture is placed in an already preheated mould and is compacted by a 75 blows of Ram on each side. The mix was kept undisturbed for 24 hours and then Marshall test was done in lab. This is helpful to find out stability and flow of sample. With replacement of RAP with various percentage of 30, 40, 50%.

Specific Gravity of the mix Gt specific gravity Gt is the specific gravity without considering air voids, and is given by:

1 + 2 + 3 + (1) = M1 M2 G1 M3 Mb + + + ܹ ܹ ܹ ܹܾ G2 G3 Gb ݐܩ

Here, W1 is the weight of coarse aggregate in the total mix, W2 is the weight of fine aggregate in the total mix, W3 is the weight of filler in the total mix, Wb is the weight of bitumen in the total mix, G1 is the apparent specific gravity of coarse aggregate, G2 is the apparent specific gravity of fine aggregate, G3 is the apparent specific gravity of filler and Gb is the apparent specific gravity of bitumen

Bulk Specific Gravity of mix Gm

The bulk specific gravity or the actual specific gravity of the mix Gm is the specific gravity considering air voids and is found out by:

(2)

= − ܹ݉ ܩ݉ ܹ݉ ݓܹ Performance Evaluation of Reclaimed Asphalt Pavement (RAP) as Aggregates when Used with Waste Cooking Oil as a Rejuvenator in Bituminous Pavements . Where, Wm is the weight of mix in air, Ww is the weight of mix in water. Where, Wm is the weight of mix in air, Ww is the weight of mix in water. Air Void percent Vv Percent Volume of bitumen Vb Air Void Percent Vv

Air voids Vv is the percentAir voidsof air voids Vv is by the volume percent in the of specimen air voids and by is givenvolume by: in the specimen and is given by: The volume of bitumen Vb is the percent of volume of bitumen to the total volume and given by:

( − )100 (3) Mb

= (4) (3) = Gb ݉ܩ ݐܩ M1+M2+M3+Mb b b PercentPercent Volume Volume of bitumenܸݒ of bitumen V V ݐܩ GNܾܸ Percent Volume of Bitumen Vb The volumeThe volume of bitumen of bitumen Vb is Vbthe ispercent the percent of volum of volume of bitumene of bitumen to the to total the volumetotal volume and given and given by: by: The volume of bitumen Vb is the percent of volume of bitumen to the total volume and given by: Mb Mb

Voids in Mineral Aggregate (VMA) (4) (4) = = Gb Gb M1+M2+M3+MbM1+M2+M3+Mb (4)

Voids in mineral aggregate VMA is the volume of voids in the aggregates, and is the sum of air voids and volume ܸܾGN ܸܾGN of bitumen, and is calculated from: Voids in Mineral Aggregate (VMA) VoidsVoids in Mineral in Mineral AggregateVoids Aggregate = in (VMA) +mineral (VMA) aggregate VMA is the volume of voids in the aggregates,(5) and is the sum of air voids and

:volumeܸݒ ofܸܾ bitumen, and is calculated fromܣܯܸ VoidsVoids in mineral in mineral aggregate aggregate VMA VMA is the isvolume the volume of voids of voidsin the in aggregates, the aggregates, and is and the issum the of sum air ofvoids air voidsand volume and volume (5) Voidsof filled bitumen,of withbitumen, and Bitumen is and calculated is (VFB) calculated from: from:

푉푀퐴Voids = filled 푉푣 + 푉푏with Bitumen (VFB) Voids filled with bitumen VFB is the = voids += in +the minera l aggregate frame work filled with the bitumen, and is (5) (5) Voids filled with bitumen VFB is the voids in the mineral aggregate frame work filled with the bitumen, calculated as: ܾܸ ݒ ܸܾܸݒܸܣܯܸ ܣܯܸ and is calculated as: × 100 (6) VoidsVoids filled filledwith Bitumenwith Bitumen (VFB) (VFB) = (6)

ܸܾ VoidsVoids filled filledwith bitumenwithܸܨܤ bitumen VFB isVFB the isvoids the voidsin the in minera the mineral aggregatel aggregate frame frame work workfilled filledwith thewith bitumen, the bitumen, and is and is ܸܯܣ calculatedcalculated as: as: 3. RESULTS AND DISCUSSIONS 3. Results and Discussions × 100 × 100 (6) (6)

= Table= 6: Result of 60/70 Grade Bitumen Rejuvenated with Various Percentages of Oil

Table 6 Result of 60/70 Grade Bitumen Rejuvenatedܸܾ ܸܾ With Various Percentages of Oil ܸܨܤ ܸܨܤTest 1% Oil 2% Oil 3% Oil ܸܯܣ ܸܯܣ Penetration 66 61 75 Test 1% oil 2% oil 3% oil 3. Results3. Results and andDiscussions DiscussionsDuctility 80 75 72 Penetration Softening Point 66 61 49 75 48 46 TableTable 6 Result 6 Result of 60/70 of Viscosity60/70Grade Grade Bitumen Bitumen Rejuvenated Rejuvenated With VariousWith Various Percentages Percentages1.3 of Oil of Oil 0.91 0.80 Ductility 80 75 72 For marshall result of replacement of 30,40,50% of RAP Softening PointTest Test 49 1% oil1% oil 48 2% oil2% oil 46 3% oil3% oil

ViscosityPenetration Penetration 1.3Table 66 7: 6630% of RAP0.91 Results 61 of61 Marshall 0.80Stability 75 Test75 (Volumetric Analysis) Binder Content Vv (%) Vb (%) VMA (%) VFB (%) DuctilityDuctility 80 80 75 75 72 72 For marshall result of replacement of4.0% 30,40,50% of RAP 6.91% 8.40% 15.31% 54.87% SofteningSoftening Point Point4.5% 49 49 6.10% 48 48 9.45% 46 46 15.55% 60.77% ViscosityViscosity 5.0% 1.3 1.3 5.21% 0.91 0.91 10.49% 0.80 0.80 15.70% 66.83% 5.5% 3.87% 11.54% 15.41% 74.89% For marshallFor marshall result result of replacement of replacement of 30,40,50% of 30,40,50% of RAP of RAP 6.0% 3.15% 12.53% 15.68% 79.91%

[231] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Table 8: For 40% of RAP Results of Marshall Stability Test (Volumetric Analysis) Binder Content Vv (%) Vb (%) VMA (%) VFB (%) 4.0% 6.50% 8.44% 14.94% 56.49% 4.5% 7.34% 9.32% 16.66% 55.95% 5.0% 4.02% 10.59% 14.61% 72.48% 5.5% 4.64% 11.49% 16.13% 71.23% 6.0% 3.04% 12.53% 15.57% 80.47%

Table 9: For 50% of RAP Results of Marshall Stability Test (Volumetric Analysis) Binder Content Vv (%) Vb (%) VMA (%) VFB (%) 4.0% 6.50% 8.44% 14.94% 56.49% 4.5% 6.10% 9.45% 15.55% 60.77% 5.0% 4.87% 10.49% 15.36% 68.30% 5.5% 5.24% 11.39% 16.63% 68.49% 6.0% 2.26% 12.64% 14.90% 84.83%

Table 10: Results of Marshall Stability Test For 30% RAP Binder Avg. Correction Corrected Avg. Vol. in cc Load (Kg) Flow Content Stability Factor Stability 4.0% 14.17 518.10 1.00 14.17 738.08 4.37 4.5% 19.20 531.18 0.96 18.43 960.31 3.50 5.0% 19.27 525.95 0.96 18.50 963.64 3.77 5.5% 14.53 502.40 1.04 15.11 787.47 3.73 6.0% 11.83 512.87 1.00 14.50 616.52 3.60

Table 11: Results of Marshall Stability Test For 40% RAP Binder Avg. Correction Corrected Avg. Vol. in cc Load (Kg) Flow Content Stability Factor Stability 4.0% 15.00 518.10 1.00 15.00 781.50 4.53 4.5% 18.60 541.65 0.93 17.30 901.23 3.83 5.0% 18.80 515.48 1.00 18.80 979.48 3.67 5.5% 16.50 502.40 1.04 17.16 894.04 3.83 6.0% 13.20 512.87 1.00 13.20 687.72 3.67

Table 12: Results of Marshall Stability Test For 50% RAP Binder Avg. Correction Corrected Avg. Vol. in cc Load (Kg) Flow Content Stability Factor Stability 4.0% 15.83 546.88 0.93 14.73 767.17 4.67 4.5% 19.03 531.18 0.96 18.15 951.97 3.57 5.0% 19.00 525.95 0.96 18.24 950.30 3.80 5.5% 17.97 502.40 1.04 18.69 973.51 3.67 6.0% 14.57 507.63 1.04 15.15 789.28 3.73 From above tables calculating the required graph data for corrected stability and flow for 30,40,50% replacement of RAP

[232] Performance Evaluation of Reclaimed Asphalt Pavement (RAP) as Aggregates when Used with Waste Cooking Oil as a Rejuvenator in Bituminous Pavements

Table 13: Graph Data of Marshall Stability Test For 30% Corrected Binder Content Marshall Flow Vv (%) VFB (%) Gm Stability 4.0% 14.17 4.37 6.91% 54.87% 2.25 4.5% 18.43 3.50 6.10% 60.77% 2.26 5.0% 18.50 3.77 5.21% 66.83% 2.27 5.5% 15.11 3.73 3.87% 74.89% 2.28 6.0% 14.50 3.60 3.15% 79.91% 2.28

Table 14: Graph Data of Marshall Stability Test For 40% Corrected Binder Content Marshall Flow Vv (%) VFB (%) Gm Stability 4.0% 15.00 4.53 6.50% 56.49% 2.26 4.5% 17.30 3.83 7.34% 55.95% 2.23 5.0% 18.80 3.67 4.02% 72.48% 2.29 5.5% 17.16 3.83 4.64% 71.23% 2.27 6.0% 13.20 3.67 3.04% 80.47% 2.28

Table 15: Graph Data of Marshall Stability Test For 50% Corrected Binder Content Marshall Flow Vv (%) VFB (%) Gm Stability 4.0% 14.73 4.67 6.50% 56.49% 2.26 4.5% 18.15 3.57 6.10% 60.77% 2.26 5.0% 18.24 3.80 4.87% 68.30% 2.27 5.5% 18.69 3.67 5.24% 68.49% 2.25 6.0% 15.15 3.73 2.26% 84.83% 2.30 Results are plotted in the graphs as per graph data calculated above:

BinderBinder Content Content vsvs Corrected Corrected MarshallMarshall StabilityStability

20.00 18.00 16.00 For 30% 14.00 For 40% 12.00

Corrected Marshall For 50%

Corrected Marshall Marshall Corrected 10.00

3.5 4.5 5.5 6.5

BinderBinder Content Content

Fig. 1: 30,40,50% RAP Corrected Stability Fig 1. 30,40,50% RAP corrected stability [233]

Binder Content vs Marshall Flow

5.00

4.50 4.00 For 30% 3.50 3.00 For 40% Marshall Flow 2.50 For 50% 3.5 5.5 Binder Content

Fig 2 30,40,50%RAP of Marshall Flow

8.00% 7.00% 6.00%

5.00% Vv(30%)

4.00% Vv(40%) 3.00% Vv(50%) 2.00% 1.00%

3.0 5.0 7.0

Fig 3 30,40,50% RAP for air voids percent

BinderBinder ContentContent vs Corrected MarshallMarshall Stability

20.0020.00 18.0018.00 16.0016.00 For 30% 14.00 14.00 For 40% 12.0012.00 For 50%

Marshall Corrected 10.00 For 50%

Marshall Corrected 10.00 3.5 4.5 5.5 6.5 3.5 4.5 5.5 6.5

Binder Content Binder Content

Fig 1. 30,40,50% RAP corrected stability Fig 1. 30,40,50% RAP corrected stability e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Binder Content vs Marshall Flow Binder Content vs Marshall Flow 5.00

4.505.00

4.004.50 For 30% 3.504.00 For 30%40% 3.003.50 Marshall Flow 2.503.00 For 40%50% Marshall Flow 2.50 3.5 5.5 For 50%

3.5 Binder Content5.5

Binder Content

Fig 2 30,40,50%RAP of Marshall Flow Fig. 2: 30,40,50% RAP of Marshall Flow

Fig 2 30,40,50%RAP of Marshall Flow 8.00% 7.00% 8.00% 6.00% 7.00% 5.00% Vv(30%) 6.00% 4.00% Vv(40%) 5.00% 3.00% Vv(30%) 4.00% Vv(50%) 2.00% Vv(40%) 3.00% 1.00% Vv(50%) 2.00% 3.0 5.0 7.0 1.00% Fig. 3: 30,40,50% RAP for Air Voids Percent Fig 3 30,40,50% RAP for air voids percent 3.0 5.0 7.0 90.00% 90.00% Fig 3 30,40,50%85.00% RAP for air voids percent 85.00% 80.00% 80.00% 75.00% 75.00% VFB 70.00% VFB 70.00% (30%) 65.00% (30%) 65.00% 60.00% VFB(40%) 60.00% VFB(40%) 55.00% 55.00% 50.00% 50.00% 3.5 4.5 5.5 6.5 3.5 4.5 5.5 6.5

Fig.fig 4: 4 30,40,50%RAP 30,40,50%RAP for VFB for VFB fig 4 30,40,50%RAP for VFB

2.31 2.31 2.30 2.30 2.29 2.29 2.28 2.28 2.27 Gm For 30% 2.27 2.26 Gm For 30% 2.26 Gm For 40% 2.25 Gm For 40% 2.25 2.24 Gm For 50% 2.24 2.23 Gm For 50% 2.23 2.22 2.22

3.5 4.5 5.5 6.5 3.5 4.5 5.5 6.5 Fig. 5: Bulk Specific Gravity of 30,40,50%RAP Fig 5 bulk specific gravity of 30,40,50%RAP [234] Fig 5 bulk specific gravity of 30,40,50%RAP Table 16 results carried out for best proportion of replacement as per standards Table 16 results carried out for best proportion of replacement as per standards

parametera Standard mix 30% RAP 40% RAP 50% RAP Standard limits parametera Standard mix 30% RAP 40% RAP 50% RAP Standard limits

OBC – 5.09% OBC-5.31% OBC-5.0% OBC-5.73% OBC – 5.09% OBC-5.31% OBC-5.0% OBC-5.73%

Marshall stability @ 17.8084KN 16.3982KN 18.8KN 17.06 KN 6.52KN Marshall stability @ 17.8084KN 16.3982KN 18.8KN 17.06 KN 6.52KN OBC minimum OBC minimum

VFB@OBC 66.028 71.8218 72.48 76.0064 50-75 VFB@OBC 66.028 71.8218 72.48 76.0064 50-75

Flow @ OBC 3.7874 3.7452 3.67 3.6976 2-4 Flow @ OBC 3.7874 3.7452 3.67 3.6976 2-4

Performance Evaluation of Reclaimed Asphalt Pavement (RAP) as Aggregates when Used with Waste Cooking Oil as a Rejuvenator in Bituminous Pavements

Table 16: Results Carried Out for Best Proportion of Replacement as Per Standards Standard Mix 30% RAP 40% RAP 50% RAP Parametera Standard Limits OBC-5.09% OBC-5.31% OBC-5.0% OBC-5.73% Marshall stability @ OBC 17.8084KN 16.3982KN 18.8KN 17.06 KN 6.52KN minimum VFB@OBC 66.028 71.8218 72.48 76.0064 50-75 Flow @ OBC 3.7874 3.7452 3.67 3.6976 2-4

4. SUMMARY & CONCLUSION 1. From obtained results of conducted test gives the positive result for considered proportion of RAP. 2. Rejuvenation of waste cooking oil if found optimum at 2%. 3. When 2% 60/70 grade bitumen is rejuvenated with waste cooking oil. Marshall tests shows that 40% replacement of Aggregates with RAP is ideal.

REFERENCES [1] Saride,S,. Deepti, T,.Rao S., Prasad,S.C,. J, S, R.Babu,D. 2014. Evaluation of fly-ash-treated reclaimed asphalt pavement for design of sustainable pavement bases an indian perspective., Geo-Congress 2014 Technical Papers, GSP 234 [2] Taha,R,, Harthy,A.A, Al-Shamsi,K., and Al-Zubeidi,M., 2002. Cement Stabilization of Reclaimed Asphalt Pavement Aggregate for Road Bases and Subbases. Journal of Materials in Civil Engineering, Vol. 14, No. 3, June 1, 2002. [3] Pradyumna,T.A., Mittal,A., Jain,P.K., 2013. Characterization of Reclaimed Asphalt Pavement (RAP) for Use in Bituminous Road Construction. 2nd Conference of Transportation Research Group of India (2nd CTRG), Procedia - Social and Behavioral Sciences 104 ( 2013 ) 1149 – 1157 [4] Chiu, C.T., Hsu, T.H., Yang,W.F., 2008. Life cycle assessmenton using recycled materials for rehabilitating asphalt pavements. Res. Conserv. Recycl. 52 (3), 545e556. [5] Gnanendran, C. T. and Woodburn, L. J.2003. Recycled Aggregate for Pavement Construction and the Influence of Stabilization. Proceedings- Conference of the Australian Road Research Board, v 21, 2003, p 1755-1768. [6] Lotfi, H. and Witczak, M. W. 1985. Dynamic Characterization of Cement-Treated Base and Subbase Materials. Transportation Research Record, n 1031, p 41-48. [7] Taha, R., Al-Harthy, A., Al-Shamsi, K. and Al-Zubeidi, M. 2002. Cement Stabilization of Reclaimed Asphalt Pavement Aggregate for Road Bases and Subbases. Journal of Materials in Civil Engineering, v 14, n 3, May/June, 2002,pp 239-245 [8] Gonzalo,V. Félix,P.J., Rodrigo,M., Experimental Study Of Recycled Asphalt Mixtures With High Percentages Of Reclaimed Asphalt Pavement. November 13,2009,Annual Meeting of the Transportation. [9] Sadeeq,J.A., Kaura,J.M., Joshua,O., and Rabilu,A., Recycling of Reclaimed Asphalt Pavement (RAP) with Rice Husk Ash (RHA)/Ordinary Portland Cement (OPC) Blend As Filler. Volume 8, No. 4, 2014,Jordan Journal of Civil Engineering. [10] Anand J. Puppala, L R. H, and Potturi,.A.K., Resilient Moduli Response of Moderately Cement-Treated Reclaimed Asphalt Pavement Aggregates. Journal of materials in Civil Engineering, ASCE, July-2011. Vol. (23), pp. 990-998. [11] IRC: 37-2012, Guidelines for the Design of Flexible Pavements. Third Revision, Indian Roads Congress, July 2012, New Delhi. [12] Taha, R., Ali, G., Basma, A., and Al-Turk, O.1999. Evaluation of reclaimed asphalt pavement aggregate in road bases and subbases. Transportation Research Record 1652, 1, 7th Int. Conf. on Low-Volume Roads, Transportation Research Board, National Research Council, Washington, D.C., 264–269.

[235] Irrigation Water Productivity in Wan Command Area in Maharashtra, India: A Case Study

Aman Tiwari1, Abhinav Prakash2, Dr. Ashutosh Upadhayaya3 and Dr. L.B. Roy4 1,2M.Tech 4th Semester, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 3Senior Scientist, ICAR Research Complex for Eastern Region, Patna, Bihar, India 4Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected]

ABSTRACT Water shortage is one of the biggest problems faced by Maharashtra state along with some other states. In this state, there is a huge amount of shortage of drinking water along with the non- availability of water for crops. The adverse effect of non - availability of water can be easily seen in agriculture sector of the state. There is requirement of advancement in technologies of crop cultivation along with the efficient use of water in crop cultivation. There is a need to adopt water saving technologies or change in cropping pattern which can suit the water availability. It is necessary to workout water productivity for the state as computed for the Wan River command area for different crops like Wheat, Maize, Soyabean, Sunflower, Groundnut etc. grown in different seasons, namely, Rabi, Kharif and Hot-weathered. The present study is related to the command area of the Wan irrigation scheme in Maharastra. The wan river is a river of central India. It is a tributary of Puma river, which in turn is a major tributary of Tapti river. It discharges into the Puma river at Buldhana district of Maharashtra. There is a dam across this river, called Wan dam and is situated in Ankola, Maharashtra. For different crops water productivity, benefit cost ratio has been computed. Based on this, it is recommended to grow crops according to the water productivity and benefit cost ratio. In thepresent case it has been found that wheat and maize have resulted into good benefit cost ratios. The benefit cost ratio of wheat is 1.14. Maize is a crop which grows in all season namely, Rabi, Kharif and Hot-weathered season with benefit cost ratio 1.64, 1.55, 2.05 respectively. Therefore, such crops should be given priority over other crops so as to have decent benefit cost ratios.

1. INTRODUCTION Maharashtra is a state in the western peninsular region of India occupying a large portion of the Deccan plateau. The Godavari , the KrishnaThe Narmada and Tapi are major rivers in the state and The Narmada and TapiRivers flow near the border between Maharashtra and Madhya Pradesh and Gujarat. In India, gross irrigation potential has increased about five folds since 1951 as a result of phenomenal expansion in irrigation development. Nowadays in irrigated agriculture the concept of water management focused on the approach of more crop per drop of water indicating need of increasing water productivity. The term water productivity is defined as the ratio of unit quantity of agriculture product(grain and other economic produce) over unit volume of water depleted by the crop or applied to the crop. The amount of the agriculture product might be expressed in different term like grain, biomass, money or nutritional value.

2. THE STUDY AREA The study deals with the command of Wan river irrigation project. Reservoir named Hanuman Sagaronstructed on Wan River, a tributary of Purna River. It falls under assured rainfall zone, receiving monsoon rains during June to October. The average annual rainfall of the command is 765.66 mm spread over 47 rainy days in normal condition. The climate is characterized by warm and humid during June to [236] Irrigation Water Productivity in Wan Command Area in Maharashtra, India: A Case Study October. November onwards, there is gradual decline in temperature. Cool and dry climate is observed during the months of November, December and January. March,April and May are the hottest months of the year.The average maximum and minimum temperature of the area is 47.9 0C and 120C. The climate is suitable for cultivating varieties of crop.

Table 1: Brief Information of the Wan River Irrigation Project Sr. No. Particulars 1 Village Wari 2 Taluka Telhara 3 District Akola 4 River Wan River 5 Latitude 21◦11’ 08’’ N 6 Longitude 76◦46’ 25’’ E 7 River basin Sub basin Purna, Basin Tapi 8 Catchment area 278.9 sq.Km 9 Average yearly rainfall 890.00 mm 10 Gross storage 83.465 Mm3 11 Live storage 81.955 Mm3 12 Dead storage 1.510 Mm3 13 Canals Lined left bank canal 14 Length of canal 14.13 Km 15 Gross command area 25,028 ha 16 Cultivable command area 22525 ha 17 Irrigable command area 15100 ha

Table 2: Existing Cropping Pattern of Wan River Irrigation Project Sr. No. Season % Area 1 Kharif 49 2 Rabi 49 3 HW crops 25 4 Two seasonals crop 43 5 Perennials 5

Fig. 1: Existing Cropping Pattern of Wan River Irrigation Project

[237] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 3. MATERIAL AND METHODS The primaryand secondary data related to climate, recommended crop cultivation practices and inputs were taken from the offices and documents from various websites and internet. Data related to status of input used and culturable practices followed by the farmers in the form of questionare. In order to have realistic analysis of the net monetary returns gained by the farmers from the existing crops and proportionate area under different crops in the project command, the related data was collected from the field by sample survey. After collection of all the required data all the figures of the data put in residual value method.

3.1 Residual Value Method Residual value method is also known as residual imputation model, RVM is a technique used to value water productivity where water is used as an intermediate input into production. Crop production is a dynamic process in which decisions about inputs are made sequentially. Farmers require field information on the soil water plant relationship before making rational decisions on the best crop to grow given condition of water scarcity. Euler’s theorem is a standard mathematical function that shows that if a production function involves constant returns to scale, the sum of the marginal products will actually add to the total product.

Considering a production function f(x1…….xn) and suppose it is homogenous of degree 1 (i.e. has constant returns to scale). Euler’s theorem shows that if the price (in terms of units of output) of each input i is its n marginal product f(x1…….xn), then the total cost namely ∑ i=1 xi fi (x1…….xn) is equal to the total output namelyf(x1…….xn). n ∑ i=1 xi fi (x1…….xn)= kf(x1…….xn) for all (x1…….xn). Residual value method is applied to findout the average economic value of irrigation water used in production across major crops. considering a production function y=f (x’s) in which four factors of production namely capital(k), labour(L), natural resources such as land(R) and irrigation water (W). Assuming production and prices are known and technology is constant. Py is the price of output, Px is the price of input under perfect information and assuming the farmers objective is to maximize production, the production function can be written as:

n n ∏ = ∑ i=1 PyYi- ∑ i=1 PxXi -PwQw To find the conditions for optimal profits, take the first derivative of ∏ with respect to X and set that equal to zero, d∏ /dx = Py.df(X)/dx – Px =0 If all the inputs, including water are exchanged in a comptetive market and employed in production process, the value of water will be

n PwQw = PyY - ∑ i=1 Px Xi

3.2 Mathematical Expression

Water Productivity in Rs/m3=

[238] Irrigation Water Productivity in Wan Command Area in Maharashtra, India: A Case Study 4. RESULTS AND DISCUSSION

Table 3: Cost of Cultivation, Net Monetary Returns and Economic Water Productivity of Different Crops in Wan River Command Area Base Volume of Water Sr. Output in Input in Output – Crop Period Water in B:C Ratio Productivity No. Rs/ha Rs/ha Input in Days m3/ ha (Rs/m3)

Kharif Season

1 Soyabean 110 1211.00 27500 36700 -9200 0.75 -7.59

2 Maize 120 2200.00 77500 50000 27500 1.55 12.50

3 Green gram 75 440.00 46500 34000 12500 1.39 28.40

4 Ground nut 120 1822.00 80000 64431 15569 1.24 9.00

Rabi Season

1 Wheat 120 9000.00 41400 36400 5000 1.14 0.55

2 Maize 120 6840.00 84600 51488 33117 1.64 5.00

3 Soyabean 110 7300.00 28800 40000 -11200 0.72 -1.53

4 Gram 105 6741.00 51340 34119 17221 1.50 3.00

Hot Weathered Crops

1 Maize 120 15800.00 105400 51387 54013 2.05 3.40

2 Groundnut 120 15710.00 115033 70965 44068 1.62 3.00

3 Green gram 75 9581.00 69000 38043 30957 1.81 3.00

4 Sunflower 105 13605.00 67500 49722 17778 1.35 1.30

18000 16000 14000 12000 3 10000

GIR in m 8000 6000 GIR cubic 4000 m per ha 2000 0

Fig. 2: Gross Irrigation Requirement in m3/ha for Kharif, Rabi and Hot Weathered Season

[239] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

35 35 30 30 25 3525 20 3020 15 B:C ratio 25 1015 WaterB:C ratio Productivity (Rs/m3) 20 105 Water Productivity (Rs/m3) 15 B:C ratio 05 10 Soyabean Maize Green gram Ground nut Water Productivity (Rs/m3) -50 5 Soyabean Maize Green gram Ground nut -10-5 0 -10 SoyabeanFig. Maize3: B:C Ratio Green and Watergram Productivity Ground nut for Kharif Season 6-5 -10 56 45 6 34 5 B:C ratio 23 4 Water Productivity (Rs/m3) 1 B:C ratio 32 Water Productivity (Rs/m3) 0 B:C ratio 1 2 Wheat Maize Soyabean Gram -1 Water Productivity (Rs/m3) 10 -2 Wheat Maize Soyabean Gram -10 Wheat Maize Soyabean Gram -1-23.5

-2 3 Fig. 4: B:C Ratio and Water Productivity for Rabi Season 3.5 3.52.5 3 32 2.5 B:C ratio 2.51.5 water productivity 2 B:C ratio 21 1.5 B:Cwater ratio productivity 1.50.5 water productivity 1 10 0.5 Maize Groundnut Green gram Sunflower 0.5 0 0 Maize Groundnut Green gram Sunflower Maize Groundnut Green gram Sunflower

Fig. 5: B:C Ratio and Water Productivity for Hot Weathered Season [240] Irrigation Water Productivity in Wan Command Area in Maharashtra, India: A Case Study 5. CONCLUSIONS 1. Net monetary returns and economic water productivity of the water user associations can be enhanced by change in cropping pattern within the limit of available irrigation water. 2. The study may be used as guidelines or suggesting appropriate cropping pattern to the farmers.

REFERENCES [1] Ahmed, A.U. and R.K. Sampath. 1988. “Welfare Implications of Tube well Irrigation in Bangladesh,” Water Resources Bulletin, 24(5): 1057-1063. [2] Bos, M.G. and W. Walters. 1990. “Water Charges and Irrigation Efficiencies.” Irrigation and Drainage Systems, 4: 267-278. [3] Ahmed, A.U. and R.K. Sampath. 1992. “Effects of Irrigation-Induced Technological Change in Bangladesh Rice Production,” Amer. J. Agr. Econ., 74(1): 144-157. [4] Bos, M. G., J. Vos, and R.A. Feddes. 1996. CRIWAR 2.0: A Simulation Model on Crop Irrigation Water Requirements, ILRI, Netherlands, Publication 46. [5] Brill, E., E. Hochman and D. Zilberman. 1997. “Allocating and Pricing at the Water District Level.” American Journal of Agricultural Economics, 79: 952-963. [6] Dahwan, B.D. 1988. Irrigation in India’s Agricultural Development,Sage Publications, New Delhi [7] Dinar, A., K.C. Knapp, and J. Letey. 1989. “Irrigation Water Pricing to Reduce and Finance Subsurface Drainage Disposal,” Agricultural Water Management, 16: 155-171.

[241] A Review on Factors Affecting Strength of Stone Columns in Soft Soil

Shivangi Saxena1 and L.B. Roy2 1Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Stone columns is an emerging technique in the field of ground improvement. It is extensively used to improve the engineering properties of soft soil. From recent researches it is observed that using stone columns to improve Young’s modulus, undrained cohesion and stiffness of soft clay is relatively cheaper as compared to any other treatment. Though there are several parameters that govern the ultimate load capacity of the stone column which are considered while designing the stone column, out of them the three important factors, the length to diameter (L/D) ratio, spacing of the column and encasement of columns by geogrids are discussed in this paper. For design of stone column the spacing of columns needs to be calculated which is based upon area ratio. L/D ratio is a crucial element that governs the failure mechanism of stone column. Many researchers have done rigorous work in determining optimum L/D ratio for maximizing the load carrying capacity of the columns. Another important technique is the encasement of stone column by geogrids to increase the stiffness of the columns. From studies it is found that encasing the column by geogrid increases its bearing capacity by around 50-60% (Kwa, S.F. 2018). This paper is a review work that explains the soil- column interaction when the stone column is subjected to variation in L/D ratio and type of pattern used for placing the stone columns in field. This paper also reviews the effect of encasing the column with geogrid. Keywords: Stone Column, L/D Ratio, Geogrid Encasement, Soft Clay, Column Spacing

1. INTRODUCTION With significant increase in population the need to make smart use of resources is increasing. Civil engineers need to make proper use of land available to them and if the land available does not meet required engineering properties then there should be some mechanism to improve the quality of land that is available. One such emerging technique in ground improvement is the use of stone columns to improve the load bearing capacity of the soil. Many literatures are found where researches have estimated the bearing capacity of the soil reinforced with stone columns (Hughes and Withers, 1974). Length of column is decided in such a manner so that it does not go beyond the stress concentration zone (Bouassida, 2009). From reviewed literatures it is found that lot of work has been done to find application of stone columns for different conditions of ground (Woo-Seok Bae et al., 2002). Ambily and Gandhi (2004) studied the response of column- soil system upon varying the shear strength parameters of the surrounding clay. Broms(1982) analysed the bearing capacity of soft clay by using lime- cement as admixture in stone columns. Various methods for the construction of stone columns are replacement or a displacement method. In the displacement method, also called the dry method, native soil is displaced by a vibratory probe using compressed air in lateral direction. This installation method is appropriate when the ground water level is low and firm soil is available (Fig. 1 and Fig. 2). In the replacement or wet method, native soil is replaced by stone columns in a regular pattern where the holes are constructed using a vibratory probe accompanied by a water jet. This method is shown in the Fig. 3 (Taube,).

[242] A Review on Factors Affecting Strength of Stone Columns in Soft Soil

Fig. 1: Dry–Top-Feed Method Process Schematic (Courtesy: Taube, 2002)

Fig. 2: Dry–Bottom-Feed Method Process Schematic (Courtesy: Taube, 2002)

Fig. 3: Wet–Top-Feed Method Process Schematic (Courtesy: Taube, 2002) From literatures, it is found that still not much work has been done to study the effect on ultimate load capacity of the stone columns by adding different natural and synthetic admixtures. If the strength of column can be increased by inclusion of various recyclable wastes from farms and industries, it would be a great progress for increasing the bearing capacity of ground by relatively lesser number of stone columns.

2. SOIL-COLUMN INTERACTION Stone columns can be given in two ways, floating columns and end- bearing columns. Floating columns are given when the thickness of soft soil deposit is relatively thick. In such cases rigid stratum is not present close to the ground surface. But if rigid stratum is present close to the ground surface, end- bearing columns can be adopted. The short term analysis of soil- column interaction refers to the study of bearing capacity of the foundation, but the long term analysis includes the study of drained settlement. As the time lapse, pore water is expelled. In such case model tests on floating or end bearing stone column is

[243] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) necessary to evaluate the long term settlement of the column group. Immediately after the application of load on reinforced ground surface, the column and the soil undergo settlement in elastic range which is typically undrained in nature (Deb, 2010). With further progress in deformation a parabolic arching of embankment over soft soil is witnessed which depends on column- soil stiffness ratio. Study carried out by Wood et al. suggests that load controlled tests are necessary to analyze the behavior of stone columns with dissipation of pore water.

2.1 Settlement Analysis Stone columns are mostly installed by vibration method in soft ground to improve the bearing capacity of the ground and reduce foundation settlement. Just like the study for analyzing bearing capacity is necessary, it is also necessary to study the settlement characteristics. From review of previous studies it is understood that soil beds are restrained by one- dimensional consolidation during loading. This technique has few problems associated with it. Firstly, the pore water pressure is uncontrolled and secondly, frictional resistance causes non uniform strength properties. To overcome these problems, Black, (2007) conducted experiment by preparing sample by one- dimensional consolidation and then transferred it to triaxial cell.

Fig. 5: Newly Developed Calibration Triaxial Cell Apparatus and Controlling System (Black, 2011) Triaxial cell provides system for controlled confining and pore water pressure. Fig. 5. shows setup for large triaxial cell used to test sample of 300mm diameter and 400mm height. Independent control vertical and lateral pressures was provided to give realistic approach of Ko. Confining pressure σ3 was applied by cell fluid and vertical pressure σ1 was controlled using uncontrolled loading mechanism. The material properties used in the experiment are shown in table 1.

[244] A Review on Factors Affecting Strength of Stone Columns in Soft Soil

Table 1: Material Properties (Black, 2007) Material Property Value Clay: Speswhite Kaolin clay Particle size, μm <63 Liquid limit, % 68 Plastic limit, % 34 Plasticity index, % 34 Modulus of elasticity, E’, kN/m2 4 Friction angle, ϕ, degrees 22 Undrained shear strength, kN/m2 25

Compression index, Cc 0.47

Swelling index, Cs 0.12 Basalt aggregate: crushed basalt, uniformly graded Particle size, mm 1.18- 2.36 Modulus of elasticity, E’, kN/m2 30 Friction angle, ϕ, degrees 43 Several methods of column installation, like the pre-forming frozen columns, forced intrusion and replacement method were used in this study (Black, 2007). It was seen that pre-forming results in reduction of column density due to thawing. On the other hand forced intrusion was found to be more realistic to the actual field conditions. This is because of densification of the displaced surrounding soil. This technique can only be followed for large scale model and it is difficult to set up in small-scale model. Replacement technique do not represents field conditions entirely. Study documented the settlement of a 60 mm foundation over a bed of soft clay with stone columns treatment with various column length to diameter ratio and area replacement ratio. It is observed that the settlement of columns-soil system can specifically be controlled using shorter columns with high replacement ratios or long columns with reduced area replacement. It is also found that an optimum area replacement ratio between 30% and 40% exists for the controlled settlement, and the soil–column interaction plays significant role in preventing excessive column deformations.

2.2 Failure Modes of Stone Columns Studies are carried out to study failure of the ground improved by stone columns. Single stone column can be constructed over a firm stratum under a soft soil by end bearing mechanism or as a floating column with tip of column embedded within the soft soil layer.

Fig. 4a: Failure Mechanism of a Long Stone Column Fig. 4b: Short Column with Rigid Base, Shear with Firm or Floating Support, Bulging Failure Failure (Courtesy: Ghanti & Kashliwal, 2008)

[245] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) However end bearing columns are more in practice. To give optimum design of columns one must understand the various failure mechanisms it can undergo. Fig. 4.a, shows the bulging failure of a long column with firm or floating support. In the case of a rigid short column, Fig 4.b, the main criteria controlling the failure is distribution of stress and strain bulbs that follows the “Meyerhof” and “Terzaghi” analysis. It is seen that the ground improvement can be carried out for an ultimate value of 25 times the cohesion of surrounding soil irrespective of the pattern and spacing of the columns (Chumnar,1993). In sensitive clays care has to be taken while estimating the spacing of column. A factor of safety of 3 is found to be suitable to prevent the column failure. When designing a column, lot of attention should be paid to the soil parameter which is not fulfilling the required value because this is the factor which will lead to substantial decrease in expected strength value. In very soft clays, vibro- flotation technique will cause extreme disturbance to the soil, which will highly effect the value of cohesion. The settlement of system after treatment with stone column is around 30% of the settlement without improvement. It is found that testing an individual stone column would not give correct results for the behavior of entire group of stone columns as the spacing and pattern of providing stone columns also plays important role in calculating the ultimate load capacity of the stone columns. Stone columns is highly useful technique in improving the bearing capacity of the ground but it requires lot of caution while implementing in soft clays. In such cases encasement or skirting may provide better solutions. Still, if the soil is extremely soft then engineer must opt for some other ground improvement technique because settlements of the ground after construction of stone column may go beyond permissible limits.

3. INFLUENCE OF POSITIONING OF STONE COLUMNS ON THE ULTIMATE LOAD CAPACITY Shahu and Reddy (2011) conducted a laboratory test on 15 test models of stone columns of Badarpur Quartz sand. The soil bed comprised of slurry of deposited Kaolinite clay. The columns were installed in square pattern. The experiment concluded that the bulging of column depends on position of column. Bulging will increase as we move towards peripheral columns from the center column. The plastic deformation is highest below the footing that extends up to bottom of columns. To reduce the plastic deformations in columns the most convenient choice for column material is well graded gravel due to its low drained cohesion and appropriate friction angle (Wood et al., 2000). Once the diameter of stone column is predicted another challenging task for the engineer is the prediction of pattern of stone column which is more or less guided by engineer’s experience. Once the column diameter is calculated empirically, the stone column spacing is calculated with known value of area replacement ratio. Generally column diameter ranges from 24 to 36 inches in dry method of installation for triangular and square pattern. Experiments show that stone columns at 1.5 to 2 m center to center spacing show appreciable improvement in the value of N when placed in triangular pattern where the stone column diameter is in the range of 600 to 800 mm. Variation in value of N is further analysed for spacing of 1.6m, 2.0m and 2.5m center to center by Rao and Madhira in 2010. It is found that optimum spacing should be 2 to 3 times the diameter of the stone columns.

4. INFLUENCE OF LENGTH TO DIAMETER (L/D) RATIO ON LOAD BEARING CAPACITY OF COLUMNS The L/D ratio of stone column plays crucial role in determining stability of column especially in soft soil. An experiment was conducted by Reddy in 2015 to study the effect of L/D ratio on the load bearing capacity of the column. Crushed stones were used in forming column having gravel percentage of about 5%, sand about 90% and fines 5%. Diameter of column was 20mm, compressive load was applied by strain controlled mechanism. Study showed that the ultimate load carried by the stone column depends

[246] A Review on Factors Affecting Strength of Stone Columns in Soft Soil greatly upon the L/D ratio of the column. Initially ultimate capacity increases up to certain critical L/D ratio but beyond this critical value there is no significant change in load bearing capacity of the stone column. Fattah et al. (2016) studied the behavior of ordinary and encased stone columns with changing L/D ratio. It is found that regardless of floating or end bearing columns the enclosure of columns with geogrid increases the strength by about 1.39 times and L/D ratio plays a major role in settlement of soil-column system. To understand the importance of L/D ratio we must understand the failure mechanism that the stone column may undergo. If the column is short, i.e. for smaller value of length the failure criteria is governed by stress- strain distribution curves. This study follows the Terzaghi and Meyerhoff analysis of stress distribution in subsoil system. It is also found that in case of floating stone columns with shorter length, the column becomes unstable even prior to bulging (Rudrabir and Kashliwal, 2008).

5. VARIATION IN LOAD CARRYING CAPACITY OF STONE COLUMN BY ENCASEMENT WITH GEOGRIDS The load carrying capacity of stone columns is derived from the lateral earth pressure. When extremely soft soil is present in at the site of installation of stone columns then chances of lateral bulging are high since the soilm is ynable to provide lateral confinement upto required extent. So in order to prevent the failure of column in such cases an extra lateral confinement is provided using geosynthetics/ geogrid encasing. Experiments conducted on geogrid encased stone columns suggest that load carrying capacity of columns can be increased by 50-60 % by encasing it with geogrid. The geogrid provide extra stability to stone column and reduces the settlement by about 10mm (Kwa, 2018). Soft soils are characterized by their high compressibility in the range of 0.20 to 0.40, low undrained shear strength < 40kPa, high water content 50-60 % and plasticity index 40-65%. These soils are typical to handle during construction and it is a tedious job to provide stone columns that can sustain loads in such situation. The performance of such soils can be improved by using additives in the backfill material or by reinforcing the stone column by some geotextile material which posses high strength. In case where unconfined compressive strength of the soil is less than 15kPa the geotextile/geogrid can be used to enhance lateral support. Fattah et al. 2012 conducted a test by using geogrid with roll length 25m, thickness 11.35mm and weight per unit area= 296 g/m2 . The test was conducted in two stages, firstly analysis of bearing capacity was done by reinforcing the soil only with stone column without the geogrid. The stress response was studied using Finite Element Modelling and it was found that bearing capacity of the soil was increased by 51%. Initially the stone column takes the surcharge load and after bulging the settlement will increase, this is the stage o failure. In the second stage, stone is encased with geogrid that confines the stones and sand in the column at place. From the finite element modeling it was found that there was significant improvement in the bearing capacity with respect to the previous case that was without geogrid. The ultimate load capacity with ordinary stone column was 7.1 kN/m2 at 10mm settlement whereas it was improved to 13kN/m2 at 10mm settlement for stone column encased with geogrid. Another study given by Kausar Ali (2014) explains the effect of encasing the stone column by geotextile up to certain percentage of length. Modeling was done on soft soil which was reinforced with stone column. The liquid limit of clay was 54% and plastic limit= 23 % i.e it was highly plastic soil. The test for floating column and end bearing column were performed separately in two steel tanks. The stone columns were constructed by replacement method. After the removal of soil, a woven geotextile was placed inside the hole. Stone chips were then filled inside the cavity by hammering. When the stone was encased over upper 25% length, the bearing capacity of column- soil system was increased by 5% only. When stone column was covered up to 50% of its length the load carrying capacity was increased to 50%. For fully encased stone column, the bearing capacity was found to increase only by 28%. In case of end bearing [247] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) column, an encasement length of 75% will increase the bearing capacity by 80%, whereas in fully covered column the load carrying capacity is substantially increased due to development of hoop stress.

6. CONCLUSIONS The improvement in bearing capacity of the soil by inclusion of stone column is basically due to three factors. Firstly, the stiff column material like crushed stones, gravel etc. imparts higher stiffness to the soil thus increasing the ultimate load capacity. Secondly, during the installation of stone columns the surrounding soil gets compacted due to vibration during installation of columns. This causes densification of the soft soil. The third factor responsible for improving the strength of column- soil system is the vertical drains which aid in consolidation of the soil mass thus resulting in higher strength of ground. It is found that by providing the geogrid encasement, stiffness of the stone column will improve. But if the column is getting inserted by floating mechanism then some portion of geogrid (lower 25%) will not be utilized for giving encasement. This is the main reason why the floating columns are less efficient than the end bearing stone columns. It is also observed that upon adding admixtures like lime or lime- cement with stone column, the load bearing capacity of columns can be substantially increased. Apart from L/D ratio, spacing and pattern of stone column, several other factors like area ratio, length of column, thickness of mat and angle of shearing resistance of granular material effects the strength of column soil response. To find the optimized spacing of columns, stress influence zone needs to be taken in regard. Most realistic result is obtained by Mohr- Coulomb criteria which is assessed by laboratory model tests. Load carrying capacity of the column is also a function of frictional properties of column material and cohesion of surrounding soil.

REFERENCES [1] Ali, K.: Effect of encasement length on Geosynthetic Reinforced Stone Columns. International Journal of Research in Engineering and Technology.72-75 (06 June-2018). eISSN: 2319-1163. Volume:03. [2] Black, J.A., Sivakumar, V., Bell, A.: The settlement performance of stone column foundations. 909-922(2011) Geotechnique 61, No. 11. [3] Bouassida, M., Jellali, B., Porbabha, A.: Limit Analysis of Rigid Foundations on Floating Columns. 89-92(2009). DOI: 10.1061/ (ASCE) 1532-3641. [4] Broms, B.G.: Lime columns in theory and practice.149-165(1982) Proceedings International Conference of Soil Mechanos, Mexico. [5] Chummar, A.V.: Failure of foundation systems using stone columns. 85-88(June,1-4,1993) Third International Conference on Case Histories in Geotechnical Engineering, Paper no. 1.21. [6] Fattah, M.Y., Majeed, Q.G.: A study on the behavior of geogrid encased capped stone columns by the Finite Element Method. 343-350(2012) International Journal of Geomate, Volume 3, No.1, ISSN:2186-2982(P), Japan. [7] Hughes, J.M.O.,Withers,N.J.: Reinforcing of soft cohesive soils with stone columns. 42-49 (1974) Serial, Ground Engineering, Volume 7, ISSN Number:3, Publisher: EMAP Construct Limited, ISSN: 0017-4653. [8] Kwa, S.F., Kolosov, E.S., Fattah, M.Y.: Ground improvement using stone column construction encased with geogrid. 49-59 (2018) Journal of Construction of Unique Buildings and Structures. ISSN:2304-6295.3(66). [9] Rao, L., Madhira, M.: Evaluation of optimum spacing of stone columns. 759-762(2010) Indian Geotechnical Conference-2010, December 16-18, IGS Mumbai Chapter. [10] Reddy, V.P., Togati, N.V.V.K, Rao, K.M.: Critical length and capacity of stone columns using 23 factorial experimentation. 167-175(2015) International Journal of Engineering Technology, Management and Applied Sciences, Volume 3, ISSN 2349-4476. [11] Rudrabir, G., Kashliwal, A.: Ground improvement techniques with a focused study on stone column. 1-11 (2018). Dept. of Civil Engineering, VIT University pp.1-11. [12] Taube, G.M., Herridge, J.R: Stone Columns for Industrial Fills. (2002),Nicholson Construction Company, Cuddy, Pennsylvania, presented at 33rd Ohio River Valley Soil Seminar, 2002. [13] Wood, D.M., Hu, W, Nash, D.F.T.: Group effects in stone column foundations. 689-698(2000) Model tests.Geotechnique, 50(6). [248] Numerical Study on the Dynamic Behaviour of Retaining Wall Backfilled with Waste Tyre

Vikash Singh1, Brijesh Kumar Sonkar2, Vashi Ahmad3 and Agwe Michael Tobby4 1,2,4M.Tech Student, Department of Civil Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, Uttar Pradesh, India 3M.Tech Student, Remote Sensing Application Centre, Lucknow, Uttar Pradesh, India E-mail: [email protected]

ABSTRACT The discarding of waste tyres has become a remarkable dilemma due to increasing number of vehicles day by day. Since, it is non-degradable, so it creates many bad impacts on human life. The possibility of waste tyre used as a less economical option for conventional granular soil backfill for retaining wall is generally more preferred. Reuse of waste tyre in engineering projects is therefore becoming an attractive solution for these environmental concerns. The influence of total lateral earth pressure on performance of retaining under various dynamic loading conditions depends on the types of backfill soil however many lightweight fills material like geofoam, fly ash, waste tyre (in many forms) etc. are being extensively used as a backfill material, is quite important for geotechnical engineers so that the sectional dimension of retaining wall can be decided inaccurate manner which suggest the overall economy in the construction of retaining wall. The primary advantages of using these lightweight materials are reduction in total lateral thrust on wall and lateral displacement of retaining wall. In general, lightweight materials that also show good strength behaviour are the solution for such situations. In the present time, waste tyres are increasingly being used in many geotechnical applications like embankment fill, retaining wall, machine foundation and bridge abutment etc. From the previous studies it is noted that the tyre chips mixed with soil is used as backfill material for the earth-retaining structures. In the present study, a numerical simulation using OPTUM G2 (finite element based numerical tool) has been carried out to evaluate the effect of waste tyre as a backfill material on total lateral earth pressure for an 8 m high wall. From present study, it has been taken that mixing of waste tyre as a backfill material substantially reduces total earth pressure on the wall in a range of 50-54% in compared to wall backfilled with the soil. Keywords: Retaining Wall, Dynamic Earth Pressure, Waste Tyre, Numerical Modelling

1. INTRODUCTION Various soil retaining structures like retaining walls, mechanically stabilized wall, bulkheads, braced excavation and bridge abutments is quite important for geotechnical engineers because such structures play a very important role in public life. So, it is important to analyze the stability and integrity of these earth retaining structures. Retaining walls are susceptible to fail during dynamic loading conditions. It is also reported by various researchers after the earthquake (Duke & Trandafir et al., 1996, Clough & Fragaszy 1977 and Trandafir et al., 2009). During strong ground motion like an earthquake, the walls are induced itself by lateral earth pressure and inertia effect. Generally, the two design approaches are used for design practice of retaining wall by Mononobe & Okabe (Mononobe & Matsuo 1929 & Okabe 1924). The Mononobe–Okabe design approach is the extension of theory of coulomb sliding wedge. Some researchers computed seismic active earth pressure behind the retaining wall using pseudo-static method (Richard et al., 1999, Choudhury & Singh 2005 and Sima Gosh, 2008) and some others proposed pseudo-dynamic approaches (Steedman & Zong 1990, Zeng & Steedman 1993, Choudhry & Nimbalkar 2006). The deformation and displacement of the wall was influenced by dynamic loading condition (Nandkumaran 1973, Richard & Elms 1979, Nadim & Whitman 1983, Reddy et al., 1985). [249] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) In static as well as in dynamic condition, the performance of retaining wall dependence upon the type of backfill material which is more suitable to mitigate the lateral earth pressure on the wall as well as to reduce the displacement of the wall: mainly clean granular cohesionless soil is preferred. The reduced earth pressure and displacement decide the sectional dimension of retaining wall which minimizes the overall cost of construction. Disposing of these waste tyres became a global problem for every countries because the stockpiling of these tyres threats to health hazard as well as environmental hazard (Clark et al., 1991, Liu et al., 1998, Hermann et al., 2001) due to the following three reasons: (1) they occupy large volumes (2) waste tire storage can be a dangerous fire risk (3) waste tire dumps provide the breeding ground for vermin, including rats and mosquitoes. When the tire burns, it produces liquid oil and toxic smoke that are affecting the environment as well as human lives. The use of waste tires in various civil engineering applications is the beast method for reducing their stockpiling and risk associated with that disposal technique.

2. BACKGROUND Various geotechnical engineers use the waste tyre in various civil engineering applications like road embankment, retaining wall , soil reinforcement, stone columns, foundation and leachate layer (Tweedie JJ et al., 1998, Cecich V et al., 1996, Ravichandran N and Huggins L 2014, Graettinger AJ 2005, Eldin NN 1992, Bosscher J 1997 Vinot V 2013 and Bhalla G 2010). The effect of the waste tire in the reduction of earth pressure was reported by (Garge & O’ Shaughnessy, 2000, Dammala et al 2015, Reddy and Krishna 2015, Xiao et al., 2012, Reddy et al., 2016a and Reddy and Krishna 2013). Some researchers explore the various properties of the waste tire. It is found that damping ratio of soil increase with an increase in rubber content (Senetakis et al., 2012, Nakhaei et al., 2012, Ehsani et al., 2015, Li et al., 2016). The value of specific gravity for shredded tire chips is lies between 1.02 to 1.24 (Ahmed 1993, Humphery et al., 1993) Ghazavi et al., 2011, Sheikh et al., 2013), which shows less than ½ that of normal granular soil. The hydraulic conductivity was reported between 2.0 to 0.75 cm/s (Ahmed 1993, Humphery et al., 1993). The triaxial test for the shear test was experimented by Bressette (1984), Ahmed (1993) and Benda (1995) and the direct shear test by Humphery et al., (1993), Cosgrove (1995), Gebhardt(1997) and Yang et al., (2002). The value of the friction angle was reported between 150 to 380 and cohesion value at 20kPa. Reddy et al., (2015) evaluate the optimum mixing ratio of a sand-Tyre chips mixture for geo-engineering application. They find the optimum ratio results in lightweight material with 20% are better for strength parameter and compressibility behavior. Rao and Dutta (2006) reported that the aspect ratio of rubber shreds bring to a close that shred size has a minor influence on the angle of internal friction. Reddy and Krishna (2016) used tire chips as compressible inclusion in earth-retaining wall to minimize the lateral earth pressure and displacement which decide the cross-section dimension of retaining wall with reduced cost. Reddy and Krishna (2015) used recycled tire chips mixed with sand as lightweight backfill material in retaining wall through experiment. The result shows that lateral earth pressure and horizontal displacement are reduced to about 50 to 60%.

3. MATERIALS AND MATERIAL PROPERTIES For this numerical study, it is essential to model a retaining wall and soil system for both granular backfill and waste tire backfill. To explain the properties of soil, the Mohar-Coulomb Soil (M-C Soil) available in OPTUM G2 was used. The undrained condition, no cavitations cut-off, no fissures, no compression cap and flow rule for hydraulic conductivity is considered. Under undrained condition (in OPTUM G2, for drainage condition = drained/undrained in analyses with time scope = short term), the M-C model, which implies a zero change of effective mean stress. Mesh element was used to represent the retaining wall.

[250] Numerical Study on the Dynamic Behaviour of Retaining Wall Backfilled with Waste Tyre The behavior of these meshes is categorized using the rigid model. The adopted values for each materials retaining wall as well as for backfill are shown in Table 1 (Richard & Elms 1979, Yang S et al., 2002).

Table 1 Sr. No. Property Soil Waste Tyre 1 Unit Weight (Kn/m3) 20 5.73 2 Elasticity (MPa) 207.99 1.29 3 Poisson Ratio 0.03 0.28 4 Cohesion (KPa) 0 21.06 5 Friction Angle (0) 30 11 The M-C material is a solid material that may be applied both to surfaces and to lines (as a shear joint for the soil-structure interface). The M-C material assumes linear elasticity and a yield function defined by two parameters, cohesion and friction angle. The Mohar-Coulomb model offers three different kinds of elasticity: linear isotropic elasticity, non-linear isotropic elasticity, and linear anisotropic elasticity. The material properties of the concrete retaining wall were based on commonly used concrete in practice. In OPTUM G2 rigid material is used for the body of retaining wall which unit weight is 25KN/m3.

4. NUMERICAL GRIDS AND PROBLEM BOUNDARIES The numerical grid for a rigid retaining wall model used in the study is shown in figure 1. The width of the wall at bottom and top are 4 m and 1 m respectively. The height of the wall is taken as 8 m. The length of backfill is considered 2H (=16 m) to facilitate the complete shear wedge (plastic zone) formation behind the retaining wall during different peak horizontal ground acceleration. A fixed distributed load of 20 kPa in negative Y- direction is applied on backfill. The system of retaining wall and backfill is such that the face of backfill is free to move in X-direction. The horizontal movement of other faces of the model is restrained.

Fig. 1: Numerical Grid of Rigid Retaining Wall with Backfill

[251] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 5. NUMERICAL MODELLING OPTUM G2 is a finite element program for strength and deformation analysis of geotechnical boundary problem. It is possible to compute rigorous upper and lower bounds to the limit load, thus bracketing the exact solution to a usually rather narrow interval. In the present analysis (numerical modeling) elastoplastic approaches followed by initial stress is taken with long term time scope. The initial stresses in the ground are in many cases an important aspect of strength and deformation analysis. In geotechnics, the initial stress is usually characterized by the earth pressure coefficient:

Where and are the effective vertical and horizontal stresses respectively. For purely frictional

Mohr-Coulomb material, the bounds on K0 are the well known active and passive earth pressure coefficient:

This analysis covers higher order Gauss element type like 15-nodes Gauss as well as higher number of an element like 5000 along with load step 3. The analysis is done under mesh adaptivity with iteration and frequencies are 3 and 3 respectively.

6. SIMULATION RESULT AND DISCUSSION The system of retaining–wall are numerically modeled with the help of non-commercially available advanced finite element program, OPTUM G2. Such a program allows for the modeling of two dimensional systems of structures and soil groups under dynamic loading condition. Comparison of factor of safety (FOS) at lower bound condition and upper bound condition on retaining wall backfill with soil and rubber for various seismic excitation levels are shown in Table 2. From the table, it is noteworthy that for a given value of Kh, total stress on retaining wall backfill with waste tyre is comparatively lower than the wall backfilled with soil.

Table 2: Comparison of FOS on Retaining Wall Backfill with Soil and Rubber for Various Seismic Excitation Levels

Kh Wall Backfilled with Soil Wall Backfilled with Waste Tyre Lower Bound Upper Bound Lower Bound Upper Bound

0.12g 9.056 9.228 21.006 22.003

0.24g 4.559 4.621 10.053 10.068

0.42g 2.622 2.661 06.031 06.107

0.48g 2.003 2.335 05.277 05.343

Even in the case of retaining wall, where the peak horizontal ground acceleration is employed as 0.48g, factor of safety is found to be lesser than one when wall is backfilled with soil. However, then the same was backfilled with waste tyre and simulated for peak horizontal ground acceleration of 0.48g, factor of safety is found to be more than three. This particular observation shows that retaining wall backfilled with waste tyre are a having greater factor of safety that the wall backfilled with soil.

[252] Numerical Study on the Dynamic Behaviour of Retaining Wall Backfilled with Waste Tyre

Fig. 2: Total Lateral Earth Pressure on Retaining Wall in Case of (a) Soil and (b) Tyre Comparison of total lateral earth pressure on the retaining wall with soil or waste tyre is shown in figure 2. It can be found that total lateral earth pressure on wall increases from top to bottom in both the cases in the soil backfill as well as in waste tyre. On increasing the value of peak ground acceleration (Kh), the value of lateral earth pressure increases from top to bottom in both the cases like soil backfill as well as tyre backfill but the reduction in total thrust is less in case of waste tyre as compared to sand backfill. Total lateral pressure on the wall is computed by calculating the area under each curve and reduction in total lateral thrust is calculated. From the above calculation, it is found that a reduction of lateral pressure in case of waste tyre is found in the range of 50 to 54% as compared to sand backfill.

7. CONCLUSION The present study shows the effectiveness of rigid retaining wall backfilled with soil and waste tyre under

Kh = 0.12g, 0.24g, 0.42g and 0.48g in terms of total lateral pressure on an 8m high wall retaining wall. In all cases of wall backfilled with waste tyre are found to be safer than the wall backfilled with soil. From the comparison of the distribution of lateral eart pressure on wall backfilled with soil and waste tyre, it is noted that for a given value of Kh, lateral earth pressure on wall reduces substantially when waste tyre is used instead of soil behind the wall. Furthermore, it is worth to mention that the reduction in total lateral thrust is observed in the range of 50% to 54% for an 8m high wall with a different value of peak horizontal ground acceleration.

ACKNOWLEDGEMENT Authors would like to express my special thanks to Optum Computational Engineering (Optum CE) for providing a free academic license for OptumG2 software to perform the present study.

[253] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) REFERENCES [1] Ahmed, I. (1993). Laboratory study on properties of rubber-soils. Ph.D. thesis, School of Civil Engineering, Purdue University., West Lafayette [2] Benda, C. C. (1995). Engineering properties of scrap tires used in geotechnical applications. Rep. No. 95-1, Vermont Agency of Transportation, Montpelier, VT [3] Bhalla G, Kumar A, Bansal A (2010) Performance of scrap tire shreds as a potential leachate collection medium. J Geotech Geol Eng 28(5):661–669. [4] Bosscher J, Edill TB, Kuraoka S (1997) Design of highway embankments using tire chips. J Geotech Geoenviron Eng 123(4):297–304. [5] Bressette, T. (1984). Used tire material as an alternative permeable aggregate. Rep. No. FHWA/CA/TL-84/07. Office of Transportation Laboratory, California Department of Transportation, Sacramento, CA [6] Cecich V, Gonzales L, Hoisaeter A, Williams J, Reddy K (1996) Use of shredded tires as lightweight backfill material for retaining structures. Waste Manag Res 14:433–451. [7] Choudhury, D. and Nimbalkar, S.S. (2006). “pseudodynamic Approach of Seismic Active Earth Pressure Behind Retaining Wall”, Geotechnical and Geological Engineering, Vol. 24, 1103–1113. [8] Choudhury, D. and Singh, S. (2005). “New Approach for Estimation of Static and Seismic Active Earth Pressure”, Geotechnical and Geological Engineering, Springer, Netherlands. [9] Clark, C., Meardon, K., and Russell, D. (1991) ―Burning Tires for Fuel and Tire Pyrolysis‖, Report by Pacific Environmental Services for the U.S. Environmental Protection Agency. [10] Clough, G.W. and Fragaszy, R.J. (1977). “A Study of Earth Loadings on Flooding Retaining Structures in the 1971 San Fernando Valley Earthquake”, Proceedings, 6thWorld Conference on Earthquake Engineering, New Delhi, India, 2455–2460. [11] Cosgrove, T. A. (1995).“Interface strength between tire chips and geomembrane for use as a drainage layer in a landfill cover.”Proc., Geosynthetics’95, Vol. 3, Industrial Fabrics Association International, MN, 1157–1168. [12] Dammala P, Reddy SB and Krishna AM(2015) Experimental investigation of the applicability of sand tire chip mixtures as retaining wall backfill. In Proceedings of the International Foundations Congress and Equipment Expo 2015 (IFCEE 2015), San Antonio, TX, USA (Iskander M, Suleiman MT, Anderson JB and Laefer DF (eds)). American Society of Civil Engineers (ASCE), Reston, VA, USA, Geotechnical Special Publication 256, pp. 1420–1429. [13] Duke, C.M. and Leeds, D.J. (1963). “Response of Soils Foundations, Earth Structures to the Chilean Earthquake of 1960”, Bulletin of the seismological society of America, Vol. 53, No. 2. [14] Ehsani, M., Shariatmadari, N., and Mirhosseini, S. M. (2015).“Shear modulus and damping ratio of sand-granulated rubber mixtures.” J. Cent. South Univ., 22(8), 3159–3167. [15] Eldin NN, Senouci AB (1992) Use of scrap tires in road construction. J Constr Eng Manag (ASCE) 118(3):561–576 [16] Foose, G. J., Benson, C. H., and Bosscher, P. J. (1996). Sand reinforced with shredded waste tires. J. Geotech. Eng., 10.1061/(ASCE)0733- 9410(1996)122:9(760), 760–767. [17] Garge, V.K. & O’ Shaughnessy, V. (2006). Tyre Reinforced Earthfill. Part 1: Construction of a Test Fill, Performance and Retaining wall design. Canadian Geotechnical Journal 37:75-96. [18] Gebhardt, M. A. (1997). Shear strength of shredded tires as applied to the design and construction of shredded tire stream crossings. M.S. thesis, Iowa State Univ., Ames, IA. [19] Genan Business & Development A/S. (2012). Scrap tires.” 〈http://www. genan.eu/tyres-2.aspx〉 (Apr. 18, 2013). [20] Ghazavi, M., Ghaffari, J., and Farshadfar, A. (2011). Experimental determination of waste tire chip-sand-geogrid interface parameters using large direct shear tests. 5th Symposium. on Advances in Science and Technology, Khavaran Higher Education Institute, Mashhad, Iran.k [21] Gotteland, Ph., Lambert, S., and Salot, Ch. (2008). Investigating the strength characteristics of tire chips – sand mixtures for geo-cellular structure engineering.” Scrap tire derived geo-materials—Opportunities and challenges, Taylor & Francis Group, London. [22] Gosh, S. (2008). Pseudo-static analysis of rigid retaining wall for dynamic active earth pressure. The 12th international conference of “International Association for Computer Methods and Advances in Geomechanics”, October 1-6, 2008, Goa, India [23] Graettinger AJ, Johnson PW, Sunkari P, Duke MC, Effinger J (2005) Recycling of plastic bottles for use as a lightweight geotechnical material. Manag Environ Qual 16(6):658–669 [24] Huggins E, Ravichandran N (2011) Numerical study on the dynamic behavior of retaining walls backfilled with shredded tires. In: ASCE proceedings of GeoRisk 2011, June 26–28, 2011, Atlanta, Georgia d 2011000, Reston. [25] Humphrey DN, Sandford TC, Cribbs MM, Gharegrat H, Manion WP (1992) Tire chips as lightweight backfill for retaining walls—phase I. Dept. of Civil Engineering, University of Maine, Orono. [26] Liu, H., Mead, J., and Stacer, R. (1998). Chelsea―Center for Recycling and Economic Development Environmental Impacts of recycling rubber In Light Fill Applications‖, Summary & Evaluation Of the Existing Literature University of Massachusetts. [27] Mononobe, N. and Matsuo, H. (1929). “On the Determination of Earth Pressures During Earthquakes”, Proceedings of World Engineering Congress, Tokyo Vol. 9. 177–189.

[254] Numerical Study on the Dynamic Behaviour of Retaining Wall Backfilled with Waste Tyre

[28] Nakhaei, A., Marandi, S. M., Kermani, S. S., and Bagheripour, M. H. (2012). “Dynamic properties of granular soils mixed with granulated rubber.”Soil Dyn. Earthquake Eng., 43(4), 124–132. [29] Nandkumaran, P. (1973). “Behaviour of Retaining Walls under Dynamic Loads”, Ph.D. Thesis, University of Roorkee, Roorkee. [30] Okabe, S. (1924). “General Theory of Earth Pressures”, Japan Society of Civil Engineering, Journal, Vol. 10, No. 6, 1277–1323. [31] Rao GV and Dutta RK(2006) Compressibility and strength behavior of sand–tire chips mixtures.Geotechnical and Geological Engineering24(3): 711–724 [32] Ravichandran N, Huggins L (2014). Applicability of shredded tire chips as a lightweight retaining wall backfill in seismic regions. In: Proceedings of geo-congress (GSP 234), ASCE, Atlanta [33] Reddy SB and Krishna AM(2013) Numerical simulations of earth-retaining structures using EPS geofoam inclusions. Proceedings of Indian Geotechnical Conference. IGS Roorkee Chapter, Roorkee, India. [34] Reddy SB, Kumar DP, Krishna AM (2015) Evaluation of optimum mixing ratio of sand–tire chips mixture for geo-engineering applications. J Mater Civ Eng. [35] Reddy SB, Kumar DP and Krishna AM(2016a) Evaluation of the optimum mixing ratio of sand–tire chips mixture for geo- engineering applications. Journal of Materials in Civil Engineering, ASCE28(2), paper no. 1335, http://dx.doi.org/10.1061/ (ASCE)MT.1943-5533.0001335. [36] Reddy, R.K., Saran, S. and Viladkar, M.N. (1985). “Prediction of Displacements of Retaining Walls Under Dynamic Conditions”, Bull. of Indian Society of Earthquake Technology, paper No. 239, Vol. 22, No. 3. [37] Richard, R.J. and Elms, D. (1979). Seismic behavior of gravity retaining wall. Journal of the Geotechnical Engineering. Division, ASCE, Vol. 105, No. GT4, 449-464. [38] Richard, R., Huang, C., and Fishman, K.L. (1999). “Seismic Earth Pressures on Retaining Structures”, Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 125(9), 771–778. [39] Senetakis, K., Anastasiadis, A., and Pitilakis, K. (2012).“Dynamic properties of dry sand/rubber (SRM) and gravel/rubber (GRM) mixtures in a wide range of shearing strain amplitudes.”Soil Dyn. Earthquake Eng., 33(1), 38–53. [40] Sheikh, M. N., Mashiri, M. S., Vinod, J. S., and Tsang, H. H. (2013). Shear and compressibility behavior of sand-tire crumb mixtures. J. Mater. Civ. Eng., 10.1061/(ASCE)MT.1943-5533.0000696, 1366–1374. [41] Shrestha, S. et al. (2016). Design and Analysis of retaining wall backfilled with a shredded tire and subjected to earthquake shaking. Soil Dyn. And Earthquake Engineering 90 (2016), 222-239. [42] Steedman, R.S. and Zeng, X. (1990). “The Influence of Phase on the Calculation of Pseudo-static Earth Pressure on a Retaining Wall”, Geotechnique, 40(1), 103–112. [43] Trandafir, A.C., Kamai, T. and Sidle, R.C. (2009). “Earthquake Induced Displacements of Soil Retaining Walls and Anchored-Reinforced Slopes”, Soil Dynamics and Earthquake Engineering, 29, 428–437. [44] Tweedie JJ, Humphrey DN, Sandford TC (1998) Tire shreds as retaining wall backfill, active conditions. J Geotech Geoenviron Eng (ASCE) 124(11):1061–10703. Cecich V, Gonzales L, Hoisaeter. [45] Vinot V, Singh B (2013) Shredded Tyre-Sand as fill material for embankment applications. J. Environ. Res. Develop. 7(4A): 1622–1627. [46] Xiao, M., Bowen, J., Graham, M., and Larralde, J. (2012). Comparison of seismic responses of synthetically reinforced walls with tire-derived aggregates and granular backfills. J. Mater. Civ. Eng., 10.1061/ (ASCE)MT.1943-5533.0000514, 1368–1377. [47] Yang, S., Lohnes, R. A., and Kjartanson, B. H. (2002). Mechanical properties of shredded tires. Geotech. Test. J., 25(1), 44–52. [48] Zornberg, J. G., Viratjandr, C., and Cabral, A. R. (2004).“The behavior of tire shred-sand mixtures.”Can. Geotech. J., 41(2), 227–241.

[255] Effect of Commercial Traffic Overloading on Pavement Performance

Gautam Prakash1 and S.K. Suman2 1Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT The need to transport maximum amount of goods in a trip to make larger profits has enabled the transporters to supply much heavier loads by the trucks. Moreover, the number of commercial vehicles plying on the roads has been on an increase at an alarming rate. The growth of these heavy and multi-axle vehicles certainly has a deteriorating effect on the pavement performance. Through this research, an effort has been made to analyse the consequences of overloading of commercial vehicles (beyond the legal limit) by studying the Vehicle Damage Factor (VDF) values of three consecutive years for the Patna-Bakhtiyarpur four-lane section (50.7 km) of NH 30 situated in Bihar, India. The VDF values, calculated by obtaining the load spectrum data from the toll plaza situated at the Begumpur area of the highway, were used in the computation of cumulative design traffic (N) for the three consecutive years (2015–16, 2016–17 & 2017–18). Afterwards, with the help of KENPAVE software, the service life of the highway after each of the 3 years was calculated and the extent of the deterioration due to overloaded commercial vehicles was figured out. The results showed that the remaining service life of the highway which stood at 18.32 years at the end of 2015–16, reduced to 15.39 years and 13.10 years at the end of 2016–17 and 2017–18 respectively, which indicates the significant effects of traffic overloading on the pavement performance. Keywords: Vehicle Damage Factor, Cumulative Design Traffic, KENPAVE, Commercial Vehicles

1. INTRODUCTION A nation’s economy is heavily influenced by the quality of highway it builds. The construction of a high quality pavement reduces journey time, vehicle operating costs, and eases the mobility of goods and individuals making a region more attractive. A pavement’s behaviour depends on the characteristics of its structure (material and thickness of each pavement layer), the climatic conditions (temperature and freeze-thaw cycles), the quality of its construction, and the subgrade bearing capacity. However, it is the traffic (load intensity, axle & wheel configuration, and frequency) which is primarily responsible for problems of pavement due to heavier axle load. Heavy traffic causes the most important failures in a pavement, resulting in fatigue cracking and rutting that require rehabilitation of pavement. The effect of vehicle overloading in pavement analysis and design has been studied by several researchers. The service life of the pavements can be significantly improved by implementing strict enforcements for restricting overloading as analysed by B.M. Sharma et al. (1995). Dawid Rys et al. (2015) analysed the effect of overloaded vehicles on fatigue life of flexible pavements based on weigh-in-motion data. They concluded that an increase in percentage of overloaded vehicles from 0 to 20% results in reduction of fatigue life up to 50%. Gatot Rusbintardjo (2013) carried a sensitivity analysis to measure the influence of overloading on road damage, considering factors such as traffic load, stress at the surface due to tyre pressure, pavement layer thickness, pavement materials, subgrade soil and environment. The results showed that 150% overloading of single, dual and triple-axle truck would bring about 500, 135 and 122% level of damage respectively. The results of calculation using VDF had similar results namely 47.20,

[256] Effect of Commercial Traffic Overloading on Pavement Performance 10.30 and 7.99 times the capacity to deteriorated pavement. Hao Wang et al. (2015) evaluated the overloading traffic impact on pavement life using mechanistic-empirical analysis approach. They found a linear relationship between the overweight percentage and the reduction ratio of pavement life regardless of the variation in traffic loading and pavement structure. In other words, they implied that 1% increase of overweight traffic may cause 1.8% reduction in pavement life. J. C. Pais et al. (2013) studied the truck factors for different vehicle cases applied to a set of pavements composed of five different asphalt layer thicknesses and five different subgrade moduli. The authors concluded that the damage due to overloaded vehicles gets diminished by increasing the asphalt layer thickness. The presence of overloads was also investigated by Luis G. Fuentes et al. (2012) regarding the existence of excessive axle loads in Colombia, mainly in vehicles with three axles (a single and a tandem axle) and with six axles (a single and a tandem axle in tractor; a tridem axle in trailer). Sandy H. Straus and John Semmens (2006) concluded in their research that for every dollar invested in motor carrier enforcement efforts, there would be $4.50 saved or avoided in pavement damage.

1.1 Scope and Objectives The scope of the work is limited to the Patna-Bakhtiyarpur four-lane section (50.7 km) of NH 30 situated in Bihar, India. The major objectives of the work are: ●● To analyse the type and frequency of overloading trucks by axle load spectrum data (collected from a toll plaza). ●● To determine the VDF from the axle load spectrum data and study its effect for various class of trucks with respect to varying loading condition. ●● To assess the severity of overloading on pavement service life.

2. METHODOLOGY The methodology adopted is represented using a flow chart:

Selection of study area

Data collection

Primary data- Secondary data- axle load, traffic Axle load data analysis pavement layer volume count (legal load) thickness, CBR

VDF analysis

Stress, strain & deformation analysis

Damage analysis

Fig. 1: Flow Chart of the Methodology Adopted [257] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 3. OBSERVATIONS AND ANALYSIS

3.1 Selection of Study Area The four-lane highway stretch of NH 30 from Patna to Bakhtiyarpur is the area of interest for this research. The 50.7 km long stretch has a 35-km Greenfield alignment which bypasses the major towns along the existing road. It connects Patna to various eastern districts of Bihar.

3.2 Data Collection The various types of data collected for the research were split into primary and secondary data. Primary Data: The axle load data and the traffic volume count of single, tandem and tridem-axle vehicles were collected from the toll plaza situated at the Begumpur area of the highway, for the years 2015–16, 2016–17 and 2017–18.

Table 1: Traffic Volume Count Number of Commercial Vehicles Year Single-axle Tandem-axle Tridem-axle 2015–16 6421 104666 33710 2016–17 8346 143619 54989 2017–18 10985 198580 88258

Fig. 2: Traffic Volume Count for Single, Tandem and Tridem Axle Vehicles Secondary Data: The thickness of layers of pavement, resilient modulus and Poisson’s ratio values were taken from IRC 37 – 2018. The subgrade CBR was set as 10%.

Table 2: Pavement Layer Data Layer Thickness (mm) Resilient Modulus (MPa) Poisson’s Ratio Bituminous layer 160 3000 0.35 WMM 250 500 0.35

0.45 GSB 200 0.2 * h *Msubgrade = 234 0.35 Subgrade – 17.6 * CBR0.64 = 75 0.45 *h = thickness of (GSB+WMM) in mm. [258] Effect of Commercial Traffic Overloading on Pavement Performance

Fig. 3: Study Area from Google Maps

3.3 Vehicle Damage Factor (VDF) The VDF is a multiplier to convert the given number of commercial vehicles having different axle configurations and axle weights into an equivalent number of standard axle load repetitions. The standard axle load depends on axle configurations such as 80 kN, 148 kN and 224 kN for single, tandem and tridem axle respectively. The equations to calculate VDF values: ●● Single axle (dual wheel) = [axle load in kN / 80]4 3.1 ●● Tandem axle = [axle load in kN / 148]4 3.2 ●● Tridem axle = [axle load in kN / 224]4 3.3 The damage power of an axle load increases roughly as a fourth power with the weight of an axle with respect to standard axle load. The VDF value for a particular axle configuration was calculated by averaging the VDF values of each vehicle of that axle configuration.

Table 3: VDF Values Year Single Axle Tandem Axle Tridem Axle 2015 11.57 4.46 1.07 2016 10.79 3.68 1.01 2017 9.82 2.96 0.91

3.4 Stress, Strain and Deformation Using the secondary data from section 3.2, the compressive stress/strain, tensile stress/strain and the deformation at each layer interface was determined with the help of KENPAVE software. The compressive strain at the top of subgrade (a requisite for rutting failure) and the tensile strain at the bottom of bituminous layer (a requisite for fatigue failure) are important results related to this analysis.

3.5 Damage Analysis The damage analysis is done to find out the life of the pavement. The design life is defined in terms of the cumulative number of standard axles that can be carried before a major strengthening, capacity [259] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) augmentation or rehabilitation of the pavement is necessary. The damage analysis is based on two criteria: the fatigue cracking based on the tensile strain at the bottom of bituminous layer, and the rutting deformation based on the compressive strain on the top of the subgrade. The failure criterion for fatigue cracking is expressed as –

–f2 –f3 Nf = f1 x (Ɛt) x (E1) 3.4

Where, Nf is the allowable number of load repetitions to prevent fatigue cracking; Ɛt is the tensile strain at the bottom of the bituminous layer; E1 is the resilient modulus of the bituminous layer; and f1, f2 and f3 are constants determined from the laboratory fatigue tests. These constants are considered as damage coefficients and the suggested values are 0.414, 3.291 and 0.854 respectively by the Asphalt Institute. The failure criterion for rutting deformation is expressed as –

–f5 Nd = f4 x (Ɛc) 3.5

Where, Nd is the allowable number of load repetitions to limit rutting deformation; Ɛc is the compressive strain on the top of the subgrade; and f4 and f5 are constants determined from road tests or field performance. The values of these constants are suggested as 1.365 x 10–9 and 4.477 respectively by the Asphalt Institute.

The reciprocal of the overall damage ratio (Dr) gives the design life in years. The damage ratio is calculated by –

Dr = n/N 3.6 Where, n is the predicted/expected number of load repetitions; and N is the allowable number of load repetitions based on Eqs. 3.4 and 3.5. The design life is evaluated for both fatigue cracking and rutting deformation and the one with a shorter life controls the design. The ‘n’ value, known as predicted/expected number of load repetitions is estimated using the equation – n = E3.7 Where, r is the annual growth rate of vehicles taken as 6%; m is the design period in years; A is the initial traffic in the year of completion of construction; D is the lateral distribution factor taken as 0.5 for a two- lane two-way road; and F is the vehicle damage factor (VDF).

4. RESULTS AND DISCUSSION

4.1 Single Axle Vehicle

Point Number Location of Points

1 At the center of a wheel in Y axis

2 At the edge of the wheel in Y axis

3 At the mid of c/c distance between two wheels along Y axis

Fig. 4: Wheel Configuration and Radial Analysis Points for Single-axle Vehicle The analysis was performed on three radial points as shown in figure. The compressive strain and tensile strain values at each layer interface are tabulated below. ‘YW’ is the wheel spacing.

[260] Effect of Commercial Traffic Overloading on Pavement Performance

Table 4: Compressive Strain Due to Single-axle Vehicle At the Surface (x Radial Points Top of WMM (x 10–4) Top of GSB (x 10–4) Top of Subgrade (x 10–4) 10–4) 1 –0.378 2.583 1.607 1.894 2 –0.437 2.020 1.724 2.020 3 –0.470 1.691 1.739 2.042 For the rutting failure analysis, the maximum compressive strain at the top of subgrade was found to be 2.042 x 10–4 below the radial point 3.

Table 5: Tensile Strain Due to Single-axle Vehicle Radial Points Bottom of BC (x 10–4) Bottom of WMM (x 10–4) Bottom of GSB (x 10–4) 1 1.097 0.890 0.933 2 1.063 0.940 0.972 3 1.019 0.948 0.978 For the fatigue failure analysis, the maximum tensile strain at the bottom of bituminous layer was found to be 1.097 x 10–4 below the radial point 1.

4.2 Tandem-axle Vehicle

Point Number Location of Points 1 At the center of a wheel in Y axis 2 At the edge of the wheel in Y axis 3 At the mid of c/c distance between two wheels along Y axis 4 At one-fourth of c/c distance between two wheels along X axis Abscissa at one fourth of line joining two axles and ordinate at 5 extreme of wheel Abscissa at one fourth of line joining two axles and ordinate at 6 midpoint of line joining two wheels in Y axis 7 At the mid of c/c distance between two wheels along X axis Abscissa at midpoint of line joining two axles and ordinate at 8 extreme of wheel Abscissa at midpoint of line joining two axles in X axis and 9 ordinate at midpoint of line joining two wheels in Y axis

Fig. 5: Wheel Configuration and Radial Analysis Points for Tandem-axle Vehicle The analysis was performed on nine radial points as shown in figure. The compressive strain and tensile strain values at each layer interface are tabulated below. ‘XW’ and ‘YW’ are axle and wheel spacings respectively.

Table 6: Compressive Strain Due to Tandem-axle Vehicle Layer Radial Points At the Surface (x 10–4) Top of WMM (x 10–4) Top of GSB (x 10–4) Top of Subgrade (x 10–4) 1 –0.356 2.382 1.456 1.775 2 –0.408 1.755 1.535 1.890 3 –0.461 1.190 1.543 1.924 4 –0.305 0.207 0.864 1.450

Table 6 (Contd.)... [261] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

...Table 6 (Contd.) Layer Radial Points At the Surface (x 10–4) Top of WMM (x 10–4) Top of GSB (x 10–4) Top of Subgrade (x 10–4) 5 –0.319 0.211 0.919 1.534 6 –0.323 0.204 0.933 1.560 7 –0.236 –0.001 0.548 1.157 8 –0.238 –0.0002 0.577 1.214 9 –0.241 0.0002 0.586 1.232 For the rutting failure analysis, the maximum compressive strain at the top of subgrade was found to be 1.924 x 10–4 below the radial point 3.

Table 7: Tensile Strain Due to Tandem Axle Vehicle Layer Radial Points Bottom of BC (x 10–4) Bottom of WMM (x 10–4) Bottom of GSB (x 10–4) 1 0.967 0.745 0.882 2 0.890 0.752 0.919 3 0.787 0.736 0.929 4 0.249 0.640 0.839 5 0.185 0.670 0.906 6 0.160 0.679 0.926 7 0.118 0.566 0.808 8 0.126 0.608 0.869 9 0.128 0.622 0.888 For the fatigue failure analysis, the maximum tensile strain at the bottom of bituminous layer was found to be 0.967 x 10–4 below the radial point 1.

4.3 Tridem-axle Vehicle

Point Number Location of Points 1 Abscissa at c/c distance between two axles and ordinate at X axis Abscissa at c/c distance between two axles and ordinate at edge of 2 wheel Abscissa at c/c distance between two axles and ordinate at midpoint 3 of c/c distance between two wheels in Y axis Abscissa at one and one-fourth c/c distance between two axles and 4 ordinate at X axis Abscissa at one and one fourth c/c distance between two axles and 5 ordinate at edge of wheel Abscissa at one and one fourth c/c distance between two axles and 6 ordinate at midpoint of c/c distance between two wheels in Y axis Abscissa at one and half c/c distance between two axles and 7 ordinate at X axis Abscissa at one and half c/c distance between two axles and 8 ordinate at edge of wheel Abscissa at one and half c/c distance between two axles and 9 ordinate at midpoint of c/c distance between two wheels in Y axis Fig. 6: Wheel Configuration and Radial Analysis Points for Tridem-axle Vehicle

[262] Effect of Commercial Traffic Overloading on Pavement Performance The analysis was performed on nine radial points as shown in figure. The compressive strain and tensile strain values at each layer interface are tabulated below. ‘XW’ and ‘YW’ are axle and wheel spacings respectively.

Table 8: Compressive Strain Due to Tridem-Axle Vehicle Layer Radial Points At the Surface Top of WMM Top of GSB Top of Subgrade (x 10–4) (x 10–4) (x 10–4) (x 10–4) 1 –0.375 2.393 1.457 1.764 2 –0.428 1.761 1.537 1.880 3 –0.480 1.200 1.545 1.914 4 –0.270 0.104 0.680 1.203 5 –0.282 0.111 0.723 1.272 6 –0.285 0.110 0.735 1.294 7 –0.201 –0.019 0.372 0.820 8 –0.208 –0.018 0.390 0.858 9 –0.210 –0.018 0.396 0.870 For the rutting failure analysis, the maximum compressive strain at the top of subgrade was found to be 1.914 x 10–4 below the radial point 3.

Table 9: Tensile Strain Due to Tridem Axle Vehicle Layer Radial Points Bottom of BC (x 10–4) Bottom of WMM (x 10–4) Bottom of GSB (x 10–4) 1 0.964 0.744 0.925 2 0.887 0.767 0.998 3 0.784 0.762 1.019 4 0.200 0.636 0.861 5 0.155 0.647 0.901 6 0.141 0.649 0.914 7 0.081 0.500 0.747 8 0.085 0.534 0.795 9 0.086 0.544 0.810 For the fatigue failure analysis, the maximum tensile strain at the bottom of bituminous layer was found to be 0.964 x 10–4 below the radial point 1.

4.4 Service Life of Pavement The service life of the highway was calculated by performing the damage analysis after the years 2015–16, 2016–17 and 2017–18 by using the KENPAVE software, to ascertain the deteriorating effects of heavy commercial vehicles on the pavement performance in these three years.

Table 10: Service Life of Highway Time Frame Remaining Service Life (in Years) % Decrease in Design Life June-2015 (completion of NH) 20 0 After 1 year (2015–16) 18.32 8.40 % After 2 years (2016–17) 15.39 23.05 % After 3 years (2017–18) 13.10 34.50 %

[263] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 7: Service Life of NH 30 at the Year End The Patna-Bakhtiyarpur section of the NH 30 was completed in June 2015. The remaining service life after the years 2015–16, 2016–17 and 2017–18 were found to be 18.32, 15.39 and 13.10 years respectively, and the percentage decrease in service life was calculated as 8.40%, 23.05% and 34.50% respectively.

5. CONCLUSIONS 1. The study of the commercial traffic volume over three years indicates that there has been a rapid increase in the vehicles on the highway with an annual average growth rate of 30.8%, 37.74% and 61.27% for single, tandem and tridem-axle vehicles respectively. 2. The study of the VDF data implies that majority of the single axle commercial vehicles are over-loaded with an average VDF of 10.72 over 3 years, demanding strict loading restrictions in such vehicles. In comparison, tandem and tridem-axle vehicles have an average VDF of 3.7 and 0.99 respectively during the same period, suggesting gentle remedial measures for these types of vehicles. 3. The compressive strain at the top of subgrade (a requisite for rutting failure), is maximum in the case of single-axle vehicle (2.042 x 10–4), followed by tandem-axle (1.924 x 10–4) and tridem-axle (1.914 x 10–4) vehicle respectively. Similarly, the tensile strain at the bottom of bituminous layer (a requisite for fatigue failure), is again maximum in the case of single-axle vehicle (1.097 x 10–4), followed by tandem-axle (0.967 x 10–4) and tridem-axle (0.964 x 10–4) vehicle respectively. 4. Hence, the analysis asserts that single-axle vehicle causes more damage to the pavement in comparison to tandem and tridem-axle vehicle respectively. 5. The damage analysis indicates that the service life of the highway is reducing way faster than expected with a total decrease of 34.50% in three years. By this rate, the highway would fail earlier than its expected life of 20 years. 6. The deteriorating performance of the highway due to over-loading of commercial vehicles can be cut-short either by enforcing strict adherence to legal axle-load limit, or by encouraging the introduction of more multi-axle commercial vehicles for higher loading capacity.

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[264] Effect of Commercial Traffic Overloading on Pavement Performance

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[265] Removal of Mercury from Aqueous Solution using Pine and Cinchona Bark

Komal Rajpoot1 and S.K. Patidar2 1M.Tech. Student, Department of Civil Engineering, National Institute of Technology, Kurukshetra, India 2Professor, Department of Civil Engineering, National Institute of Technology, Kurukshetra, India E-mail: [email protected]

ABSTRACT The heavy metal contamination is a serious problem threatening human health and other organisms. A low cost and effective adsorbent can help in removal of heavy metals including mercury (Hg) from water and wastewater. In the present study, adsorption of Hg (II) ions on chemically treated pine bark and chinchona bark from aqueous media was investigated. Chemical treatment with 0.1 N NaOH was done to powdered pine bark and cinchona bark to increase its adsorption capacity. The effects of various parameters like adsorbent dose, pH, contact time and initial mercury ion concentration on adsorption of Hg (II) ions on powdered pine bark and cinchona bark were evaluated. The optimum dose was found to be 6 g/L, optimum pH was 5, optimum contact time was 90 min and at 30 ppm Hg (II) ions concentration adsorption capacity was maximum for pine bark. The maximum adsorption capacity was observed as 15.17 mg/g and maximum removal efficiency was observed as 89.23% for pine bark. For cinchona bark the optimum dose was 3.5 g/L, optimum pH was 6, optimum contact time was 120 min and for maximum removal Hg (II) ions concentration was found to be 20 ppm. Maximum adsorption capacity was found to be 22.1 mg/g and maximum removal efficiency was 76.59% for cinchona bark. It was observed that the removal efficiency of pine bark was higher than cinchona bark. Keywords: Hg (II), Pine Bark, Cinchona Bark, Chemical Treatment

1. INTRODUCTION There is rapid increase in discharge of wastewater with heavy metal ions into the environment due to fast economic growth and industrialization (Temocin et al., 2010). Among various heavy metals, mercury (Hg) is considered as one of the most toxic metal which poses great risks to both human health and environment. Mercury remain in the environment for a relatively long period and cause serious health issues in humans as well as in animals as it is toxic even at very low concentration. Mercury is discharged into the environment through natural as well as anthropogenic sources (Ekino et al., 2007). It has neurological influences as it can enter our nervous system through blood and affects the cerebrum, most interior part of the brain (Demirbas et al., 2008). Due to the serious impacts of mercury on human health, World Health Association (WHO) has set the limit for mercury in drinking water to be 0.001 mg/L (Bayramoglu et al., 2007). Thus Mercury should be removed from industrial waste before its discharge into water bodies. In India, coal industry, thermal power plants, bricks and cement industry, chloro-alkali industries and improper disposal of clinical thermometers are the sources of mercury emission in environment. Effluent discharged from various industries in industrial area of Chhattisgarh state has reported mercury value between 6.7-678 ng/mL (Mukherjee et al., 2009). Among all forms methyl mercury is most destructive to human being and animals because of its tendency to bio accumulate in the food-chain resulting in high mercury concentration in their body relative to concentration in surroundings. States like Haryana, Gujarat, Andhra Pradesh, Orissa and West Bengal have mercury level in the range of 0.058 to 0.268 mg/L in ground water which is very high as compared to the permissible limit of mercury for drinking water set by Indian Standards i.e. 0.01 mg/L (BIS, 2012).

[266] Removal of Mercury from Aqueous Solution using Pine and Cinchona Bark There are numerous conventional techniques available for the treatment of mercury containing wastewater. These techniques include filtration, precipitation with carbonate or hydroxide, ion exchange, reverses osmosis, coagulation, solvent extraction, etc. (Febrianto et al., 2009). These traditional methods have drawbacks such as low performance efficiency, high cost of chemicals and disposal problems (Huang et al., 2010). Adsorption is considered a superior method due to its simplicity, minimization of secondary waste and high-efficiency (Kurniawan et al., 2006). Pine trees are evergreen, coniferous resinous trees growing 3–80 m (10–260 ft) tall, with the majority of species reaching 15–45 m (50–150 ft) tall. Large quantities of pine products are produced annually throughout the world. Pine bark is an environmental waste which has been successfully used for removal of heavy metals such as lead, chromium, cadmium, etc. Cinchona plants belong to the family Rubiaceae and are large shrubs or small trees with evergreen foliage, growing 5–15 m (16–49 ft) in height and have medicinal values. Interactions effects of cinchona was studied in one of the prior art for the removal of lead from aqueous solution which showed antagonistic effect on efficiency of pine. (Al-Subu et al., 2002). Cinchona has also been used as catalyst in various metal removal processes (Lutz et al., 1937). In present study, the adsorption potential of powdered pine bark and cinchona bark for Hg (II) ion removal from water has been investigated. Batch mode study has been done by varying important parameters affecting adsorption process such as adsorbent dose, pH, contact time and initial Hg ion concentration. To increase the adsorption capacity of powdered barks, chemical treatment with 0.1 N NaOH was done.

2. MATERIALS AND METHODS

2.1 Pine Bark, Cinchona Bark and Reagents Activated Pine tree bark and Cinchona tree bark treated with NaOH reagent was used in present study and named as NaOH activated bark. All the reagents HgCl2, NaOH used for study were of analytical grade.

2.2 Synthetic Mercuric Stock Solution The Mercury stock solution (1000 mg/L) was prepared by dissolving required amount of HgCl2 in distilled water. Solutions of desired concentration were obtained by diluting stock mercury solution with distilled water and used throughout the study.

2.3 Preparation and Treatment of Pine Bark and Cinchona Bark Pine bark Cinchona bark was initially converted in powder form which passed through 300 mm sieve and retained on 150 mm sieve size. An accurately weighed 25 g of bark materials were poured into 500 ml conical flask containing 250 ml 0.1 N NaOH and stirred for 15 min then solution was filtered with Whatman Filter paper No-1 and barks were taken and washed for several times with distilled water. After it adsorbents were oven dried at 80°C for 3 hours. NaOH was used to increase the proportion of active surfaces. NaOH solution was increase adsorption efficiency due to increase of negatively charged hydroxyl anions. NaOH solution may also react with phenolic constituents of barks and may be phenoxy anions occur (Masri; et al., 1974).

ArOH + NaOH → ArO-Na+ + H2O (1) 2ArO- + M+2 → Ar2O2M (2) Where, Ar is the functional groups of bark and M represent metal ions. Thus the activated barks are generally having greater values. [267] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.4 Batch Study Details Adsorption studies were carried by batch experiments at room temperature. pH of mercury solution was found to be 4.43. In the first stage, experiments were conducted for adsorbent dose range from 1 to 8 g/L for pine bark adsorbent. Other parameters like pH (4.43), contact time (30 min), initial Hg (II) concentration (100 mg/L) were kept constant. The adsorption process was carried out by shaking the 250 mL Erlenmeyer flask containing 50 mL Hg ion solution and required amount of pine bark adsorbent in orbital shaker for 30 min at 120–130 rpm. After required contact time the solutions were filtered using Whatman Filter paper No-1. Adequate samples were taken from the solution and Hg ion concentration was determined using mercury analyzer to determine the optimum dose. For Pine optimum dose of 6 gm/L of pine bark, pH was investigated in the second stage keeping other parameters like adsorbent dose (6 gm/L), contact time (30 min), initial Hg (II) concentration (100 mg/L) constant. Experiments were conducted for pH range from 1 to 10. pH was adjusted using 0.1 N H2SO4 and 0.1 N NaOH. Optimum pH was found to be 5. In the third stage, experiments were performed at different contact time (30, 60, 90, 120, 150 minutes) and other parameters were kept constant. Contact time of 90 minutes was found most suitable for the mercury adsorption. In the fourth stage, effect of initial Hg (II) concentration (ranging from 10 to 400 mg/L) was investigated by keeping other parameters as constant. Same process was repeated for cinchona bark as adsorbent.

2.5 Analytical Techniques Mercury concentration was determined by PC based Mercury Analyzer HG-100 at 253.7 nm wavelength. pH of mercury solution was measured and adjusted by using Sension HACH, pH3 Meter.

2.6 Adsorption Efficiency Parameters Based on Hg ion concentration before and after adsorption (Ci and Ce, respectively in mg/L), weight of the adsorbent taken (W in gm) and volume of aqueous solution (V in liters), the amount of equilibrium adsorption of mercury (qc) was calculated using Equation 3. qc (mg/g) = (Ci – Ce )V/W (3) The mercury removal percentage (R %) was calculated using the Equation 4. R (%) = (Ci – Ce)/Ci × 100 (4)

3. RESULTS AND DISCUSSION

3.1 Mercury Ion Adsorption

3.1.1 Effect of Adsorbent Dose The effect of adsorbent dose on adsorption of mercury ions was studied by varying pine and cinchona bark dose from 1 to 8 g/L and 1 to 5 g/L respectively at room temperature and keeping all other parameters constant. The results are shown in the Figure 1. The adsorption capacity increased from 10.19 mg/g to 13.0 mg/g with an increase in pine bark adsorbent dose up to 6 g/L and decreased from 13.0 mg/g to 9.50 mg/g with further increase in dose of pine bark. For cinchona bark adsorption capacity increased from 15.10 mg/g to 17.78 mg/g with increase in dose up to 3.5 g/L and decreased from 17.78 mg/g to 11.07 mg/g till 5 g/L. This increase in adsorbed Hg metal ions may be due to increased surface area and availability of new active sites. Further when an optimum amount has been adsorbed, the adsorption capacity is decreased.

[268] Removal of Mercury from Aqueous Solution using Pine and Cinchona Bark The results on removal efficiency of variation in adsorbent dose are summarized in Figure 2. The removal efficiency by pine bark increased from 9.98 % to 76.36 % for adsorbent dose up to 6 g/L and the removal efficiency by cinchona bark increased from 15% to 61.69% for adsorbent dose up to 3.5 g/L. This increase in adsorbed Hg metal ions may be due to increased surface area and availability of new active sites (Temoçin et al., 2010). When an optimum amount has been adsorbed, the removal efficiency is decreased from 76.36 % to 74.47 % for pine bark and from 61.69 % to 54.93 % for cinchona bark with further increase in adsorbent dose.20

g) 18 /

g 20

m 16 ( g) 18 /

y 14

m 16 (

y 14 acit p 1210 acit

p Pine 10 8 Pine 8 Cinchona

tion Ca 6 Cinchona p tion Ca 6 p 4 4 22 Adsor Adsor 00 123455.566.577.5123455.566.577.5 Adsorbant Dose (g/l) Adsorbant Dose (g/l) Fig. 1: Effect of Adsorbent Dose on Adsorption Capacity (pH 4.43; Contact Time 30 min; Hg Ion Concentration 100 mg/L) 90 8090 7080 60 70 50 Pine 4060 3050 Cinchona Pine 2040

Removal Efficiency (%) 1030 Cinchona 0 20 1 2 3 4 55.566.577.58

Removal Efficiency (%) 10 Adsorbant Dose (g/l) 0 25 1 2 3 4 55.566.577.58 Adsorbant Dose (g/l) 20 Fig. 2: Effect of Adsorbent Dose on Removal Efficiency 15 (pH25 4.43; Contact Time 30 min; Hg Ion Concentration 100 mg/L) Pine 10 3.1.2 Effect of pH20 Cinchona pH plays an important role5 in defining the adsorption behavior. The effect of pH on adsorption capacity was investigated by varying15 the pH of solutions between 1 and 10. The pH was adjusted using 0.1 N 0 [269]

Adsorption (mg/g) Capacity 12345678910 Pine 10 pH Cinchona 5

Adsorption (mg/g) Capacity 12345678910 pH

g) 18 / g

m 16 (

y 14 12 acit p 10 Pine 8 Cinchona

tion Ca 6 p 4 2 Adsor 0 123455.566.577.5 Adsorbant Dose (g/l)

90 80 70 60 50 Pine 40 30 Cinchona e-Book:20 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

H2SO4 and 0.1 N NaOHRemoval Efficiency (%) 10solutions. The results are shown in the Figure 3. The adsorption capacity of pine bark increased from 9.10 mg/g0 to 13.72 mg/g with an increase in pH up to 5. For pine bark maximum removal of mercury ions were observed1 2 3 at pH 4 5. 55.566.577.58 At the pH>5 decrease in the adsorption capacity was observed. For cinchona bark adsorption capacity increased from 11.04 mg/g to 20.58 mg/g with increase in pH up to 6 and then decreased if pHAdsorbant is greater than Dose 6. (g/l)

Pine 10 Cinchona 5

Adsorption (mg/g) Capacity 12345678910 pH

Fig. 3: Effect of pH on Adsorption Capacity (Adsorbent Dose 6 g/L and 3.5 g/L for Pine Bark and Cinchona Bark Respectively; Contact Time 30 min; Hg Ion Concentration 100 mg/L) The results of removal efficiency with variation in pH are summarized in Figure 4. The removal efficiency increased from 53.32 % to 80.38 % for pine bark and from 38.26% to 71.34 % for cinchona bark with an increase in pH up to 5 and 6 respectively. When an optimum amount has been adsorbed, the removal efficiency is decreased from 80.38 % to 52.05 % for pine bark and from 71.34 % to 42.56 % for cinchona bark with further increase in pH.

90 80 70 60 50 40 Pine 30 Cinchona 20 10 Removal Efficiency (%) 0 12345678910 pH

Fig. 4: Effect of pH on Removal Efficiency (Adsorbent Dose 6 g/L and 3.5 g/L for Pine Bark and Cinchona Bark Respectively; Contact Time 30 min; Hg Ion Concentration 100 mg/L) 25 [270]

15 Pine 10 Cinchona

Adsorption (mg/g) Capacity 0 30 60 90 120 150 Contact time (Minutes)

86 84 82 80 78 76 74 Pine 72 Cinchona 70 Removal Efficiency (%) Efficiency Removal 68 66 64 30 60 90 120 150 Contact time (Minutes)

90 80 70 60 50 Removal of Mercury from Aqueous Solution using Pine and Cinchona Bark 40 Pine 3.1.3 Effect of Contact30 Time Cinchona The adsorption capacity20 at variable contact time keeping other variables constant was evaluated and results are shown in Figure10 5. The adsorption capacity increased from 13.63 mg/g to 14.20 mg/g for pine Removal Efficiency (%) bark with an increase in0 contact time up to 90 min. And for cinchona bark adsorption capacity increased from 20.43 mg/g to 20.93 mg/g12345678910 with increase in contact time up to 120 min. Adsorbed quantity was initially low and then it increased and finally becomepH constant.

15 Pine 10 Cinchona

Adsorption (mg/g) Capacity 0 30 60 90 120 150 Contact time (Minutes)

Fig. 5: Effect of Contact Time on Adsorption Capacity (Adsorbent Dose 6 g/L and 3.5 g/L for Pine Bark and Cinchona Bark86 Respectively; pH 5 and 6 for Pine Bark and Cinchona Bark Respectively; 84 Hg Ion Concentration 100 mg/L) The results of removal 82efficiency with the variation in contact time are summarized in Figure 6. The removal efficiency increased80 from 79.86 % to 83.21 % for pine bark and from 70.82 % to 72.51 % for cinchona bark with an increase78 in contact time up to 90 min and 120 min respectively and then almost become constant. 76 74 Pine 3.1.4 Effect of Initial72 Hg Ion Concentration Cinchona Effect of initial Hg ion concentration70 on the adsorption capacity was studied by varying the Hg concentration between 10–400 mg/L.(%) Efficiency Removal 68 The other parameters were kept constant and results obtained are shown in Figure 7. It was observed66 that at low mercury ion concentration (<50 ppm) adsorption capacity of both adsorbent was maximum.64 For pine bark adsorption capacity increased from 14.42 mg/g to 15.17 mg/g with an increase in initial Hg ion30 concentration 60 90 up to 120 30 ppm 150 and further decreased from 15.17 mg/g to 7.28 mg/g till 400 ppm. For cinchona bark maximum adsorption capacity observed as 22.10 mg/g at 20 ppm then further decreased from 22.10Contact mg/g time to 16.95 (Minutes) mg/g with increase in Hg ion concentration from 20 ppm to 400 ppm. The results of removal efficiency with variation in initial Hg ion concentration are summarized in Figure 8. It was observed that at low mercury ion concentration (<50 ppm) removal efficiency for both adsorbent was maximum. For pine bark removal efficiency increased from 84.80 % to 89.23 % with an increase in initial Hg ion concentration up to 30 ppm and further decreased from 89.23 % to 42.85 % till 400 ppm. For cinchona bark removal efficiency increased from 73.85 % to 76.59 % with increase in initial Hg ion concentration up to 20 ppm and further decreased from 76.59 % to 58.75 % with increase in Hg ion concentration from 20 ppm to 400 ppm.

[271] 90 80 70 60 50 40 Pine 30 Cinchona 20 10 Removal Efficiency (%) 0 12345678910 pH

15 Pine 10 Cinchona

Adsorption (mg/g) Capacity 0 30 60 90 120 150 Contact time (Minutes) e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

86 84 82 80 78 76 74 Pine 72 Cinchona 70 Removal Efficiency (%) Efficiency Removal 68 66 64 30 60 90 120 150 Contact time (Minutes)

Fig. 6: Effect of Contact Time on Removal Efficiency (Adsorbent Dose 6 g/L and 3.5 g/L for Pine Bark and Cinchona Bark Respectively; pH 5 and 6 for Pine Bark and Cinchona Bark Respectively; Hg Ion Concentration 100 mg/L)

10 Pine Cinchona 5 Adsorption (mg/g) Capacity

0 10 20 30 40 50 100 200 300 400

Hg Conc. (mg/L)

Fig. 7: Effect of Hg Ion Concentration on Adsorption Capacity (Adsorbent Dose 6 g/L and 3.5 g/L for Pine Bark and Cinchona Bark Respectively; pH 5 and 6 for Pine Bark and Cinchona Bark Respectively; Contact Time 90 100 min and 120 min for Pine Bark and Cinchona Bark Respectively) 90 80

70 [272] 60 50 40 Pine 30 Cinchona 20 10 Removal Efficiency (%) 0 10 20 30 40 50 100 200 300 400

Hg Conc. (mg/L)

10 Pine Cinchona 5 Adsorption (mg/g) Capacity

0 10 20 30 40 50 100 200 300 400

Hg Conc. (mg/L)

Removal of Mercury from Aqueous Solution using Pine and Cinchona Bark

100 90 80 70 60 50 40 Pine 30 Cinchona 20 10 Removal Efficiency (%) 0 10 20 30 40 50 100 200 300 400

Hg Conc. (mg/L)

Fig. 8: Effect of Hg Ion Concentration on Removal Efficiency (Adsorbent Dose 6 g/L and 3.5 g/L for Pine Bark and Cinchona Bark Respectively; pH 5 and 6 for Pine Bark and Cinchona Bark Respectively; Contact Time 90 min and 120 min for Pine Bark and Cinchona Bark Respectively)

4. CONCLUSIONS In present study, removal of mercury metal ions from aqueous solution using pine bark and cinchona bark was investigated. Effects of various parameters like adsorbent dose, pH, contact time, initial Hg ion concentration on adsorption of Hg (II) ions on adsorbent capacity were studied. The optimum pine bark adsorbent dose for Hg (II) ion was 6 g/L and optimum pH was 5. For cinchona bark optimum adsorbent dose was 3.5 g/L and optimum pH was 6. The adsorption of Hg ion was maximum at 20 to 30 ppm initial Hg ion concentration. The maximum Hg adsorption capacity of 22.10 mg/g was observed for cinchona bark at optimum dose of 3.5 g/L and the maximum adsorption capacity observed for pine bark was 15.17 mg/g at optimum dose of 6 g/L. The removal of Hg ion was better by pine bark adsorbent with removal efficiency up to 89.23 % as compared to removal efficiency of 76.59% by cinchona bark adsorbent. Thus the pine bark has better ability for Hg ion removal from aqueous solution and it may be used for the removal of Hg (II) ions from water and wastewater.

REFERENCES [1] Ali, G.; Duygu, O.; Celal, D.; Volkan, N.B.; Mustafa, S. and Hasan, B.S. (2009) Biosorption of Pb (II) ions from aqueous solution by pine bark, Chemical Engineering Journal, 153(1-3), 62-69. [2] Aicam, L.; Edward, A.N. and Randal, K.K. (2013) Distribution and Uptake Dynamics of Mercury in Leaves of Common Deciduous Tree Species in Minnesota, U.S.A. Environment and Science Technology, 47(18), 10462–10470. [3] Al-Asheh, S. and Duvnjak, Z. (1997) Sorption of cadmium and other heavy metals by pine bark, Journal of Hazardous Materials, 56(1-2), 35-51. [4] Al-Subu, M.M. (2002) The interaction effects of cypress (Cupressus simperirens) cinchona (Eucalyptus longifolia) and pine (Pinus halepensis) leaves on their efficiencies for lead removal from aqueous solutions, Advances in Environmental Research, 6(4), 569–576. [5] Bayramoglu, G.; Yakup, Arica M. and Bektas, S. (2007) Removal of Cd (II), Hg (II) and Pb (II) ions from aqueous solution using p (HEMA/chitosan) membranes, Journal of Applied Polymer Science, 106(1), 169-177. [6] Bhatnagar, A. and Minocha, A.K. (2006) Conventional and non-conventional adsorbents for removal of pollutants from water: A Review, Indian Journal of Chemical Technology, 13(1), 203-217. [7] Budinova, T.; Petrov, N.; Parra, J. and Baloutzov, V. (2008) Use of an activated carbon from antibiotic waste for the removal of Hg (II) from aqueous solution, Journal of Environmental Management, 88(1), 165-172. [8] Crini, G. (2006) Non-conventional low-cost adsorbents for dye removal: A Review, Bioresource Technology, 97(9), 1061-1085. [9] Cutillas, B.; Ansias, M.L.; Fernandez, C.D.; Arias, E.M. and Nunez, D.A. (2014) Pine bark as bio-adsorbent for Cd, Cu, Ni, Pb and Zn, Batch-type and stirred flow chamber experiments, Journal of Environmental Management, 144(1), 258-264.

[273] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

[10] Demirbas, A. (2008) Heavy metal adsorption onto agro-based waste materials: A Review, Journal of Hazardous Materials, 157(2), 220-229. [11] Deshicar, A.M.; Bokade, S.S. and Dara, S.S. (1990) Modified hardwickia binata bark for adsorption of mercury (II) from water, Water Research, 24(8), 1011-1016. [12] Ekino, S.; Susa, M.; Ninomiya, T.; Imamura, K. and Kitamura, T. (2007) Minamata disease revisited: an update on the acute and chronic manifestations of methyl mercury poisoning, Journal of the Neurological Sciences, 262(1), 131-144. [13] Febrianto, J.; Kosasih, A.N.; Sunarso, J.; Ju, Y.H.; Indraswati, N. and Ismadji, S. (2009) Equilibrium and kinetic studies in adsorption of heavy metals using biosorbent: a summary of recent studies, Journal of Hazardous Materials, 162(2), 616-645. [14] Lutz, G. (1933) cinchona bark alkaloid derivative, Patent No. US2072004. [15] Isabel, B. (2004) Application of pine bark as a sorbent for organic pollutants in effluents, Management of Environmental Quality, International Journal of Environmental Science and Technology, 15(5), 491-501. [16] Jumle, R.; Narwade, M.L. and Wasnik, U. (2002) Studies in adsorption of some toxic metal ion on citrussinensis skin and coffea arabica huck: Agriculture byproduct, Asian Journal of Chemistry, 14(1), 1257-1262. [17] Krishnan, K.A. and Anirudhan, T. S. (2002) Removal of mercury (II) from aqueous solutions and chlor-alkali industry effluent by steam activated and sulphurised activated carbons prepared from bagasse pith, Journal of Hazardous Materials, 92(2), 161-183. [18] Kurniawan, T. A.; Chan, G. Y.; Lo, W. H. and Babel, S. (2006) Comparisons of low-cost adsorbents for treating wastewaters laden with heavy metals, The Science of the Total Environment, 366(2), 409-426. [19] Lucy, S. (2018) Removal of heavy metals (Cu, Pb) from aqueous solutions using pine (Pinus halepensis) sawdust, Equilibrium, kinetic and thermodynamic studies, Environmental Technology & Innovation, 12(1), 91-103. [20] Manohar, D. M.; Krishnan, K. A. and Anirudhan, T. S. (2002) Removal of mercury (II) from aqueous solutions and chlor- alkali industry wastewater using 2-mercaptobenzimidazole-clay, Water Research, 36(6), 1609-1619. [21] Masri, M. S.; Reuter, F. W. and Friedman, M. (1974) Binding of metal cations by natural substances, Journal of Applied Polymer Science, 18(3), 675-681. [22] Oleksandr, K. (2010) Adsorption of heavy metals by a sorbent based on pine bark, Journal of Water Chemistry and Technology, 32(6), 336-340. [23] Sari, A. and Tuzen, M. (2009) Removal of mercury (II) from aqueous solution using moss (Drepanocladus revolvens) biomass, equilibrium, thermodynamic and kinetic studies, Journal of Hazardous Materials, 171(1), 500-507. [24] Sreedhar, M. K.; Madhukumar, A. and Anirudhan, T. S. (1999) Evaluation of an adsorbent prepared by treating coconut husk with polysulphide for the removal of mercury from wastewater, Indian Journal of Engineering and Materials Sciences, 6(5), 279-285. [25] Ucun, H.; Bayhan, Y.K.; Kaya, Y.; Cakici, A. and Algur, O.F. (2002) Biosorption of lead (II) from aqueous solution by cone biomass of pinus sylvestris, Desalination, 154(3), 233-238.

[274] Early Contractor Involvement (ECI) as a Construction Project Delivery Method: An Overview

Siddhesh D. Sagvekar1 and Dr. A.S. Wayal2 1M.Tech. Construction Management Scholar, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India 2Professor, Department of Civil and Environmental Engineering, Veermata Jijabai Technological Institute, Matunga, Mumbai, India E-mail: [email protected], [email protected]

ABSTRACT Early contractor involvement (ECI) is rising as a new project delivery methodology for various complicated projects. ECI refers to the involvement of a contractor at an early stage of project development, to work in conjunction with the client and/or consultant. There are different project delivery options, which include the traditional strategies like Design-Build (DB), Construction Management in danger (CMR), Alliance and Swiss challenge method. However, these all contracting practices usually separate the design and construction processes and thus hinder the integration of construction knowledge into the design. This has led to a requirement for different project delivery methods. This article, therefore, aims to contribute towards understanding of early contractor involvement strategy. Also a summary of worldwide use of ECI as a construction project delivery methodology as different versions of ECI are employed in different countries. Keywords: Early Contractor Involvement, Design-Build, Construction Management at Risk, Alliance, Swiss Challenge Method

1. INTRODUCTION A project delivery method is outlined as a way for procurement by that the owner’s assignment of ‘‘delivery’’ risk and performance for design and construction, to the extent of scope outlined underneath procurement, transferred to a different party (parties). These parties usually are a design entity who takes liability of the design and a contractor who takes liability for the performance of the construction. There are several factors that may be used to define project delivery options. By using a different combination of these factors, each option can be uniquely defined. ECI is also a combination of different delivery options. The contractor in the ECI approach can be engaged through various methods [15]. The concept of Early Contractor Involvement (ECI) was initially used in the UK in 1998 and later adopted in many countries like Australia after 2005. ECI strives to involve the contractor, immediately after the concept stage and before the statutory procedures/approvals are in place. According to Song et al. (2009) [5], ECI aims at developing long term relation-ships between project participants throughout the design and construction phase, and delivering the most effective value. Contractors typically have a better level of construction experience compared to the owners and designers because of their comprehensive knowledge of construction materials, strategies and costs, and when they ultimately become answerable for the construction operations, their input to design can have a right away impact on the quality of their own designing additionally as construction performance [9]. Sødal et al. (2014) [16] assessed many advantages and downsides for the design team once the contractor is concerned within the early phases of design.

[275] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 2. TYPICAL PROJECT DELIVERY METHODS AND EARLY CONTRACTOR INVOLVEMENT The selection of most appropriate project delivery method is dependent on number factors and project requirements for a particular project. Some of the forms of ECI are a) Design-build (DB) wherein Contractor/ Developer has all the liability of design and construction. Only final output is specified by the employer. b) Construction management at risk (CMR) is a delivery method whereby an Architect/Engineer is chosen to design the project and separately a construction manager at risk is chosen to serve as a general contractor. The construction manager (CM) assumes the risk for construction at a guaranteed price and provides design phase consultation in evaluating prices, schedule, implications of different designs and systems and materials throughout and after design of the facility. c) An alliance is a delivery method whereby owner work collaboratively with one or more service suppliers in one integrated team so as to accomplish a particular project. d) Swiss Challenge is a delivery method, wherein interested one contractor/ developer incurs cost of preparation of DPR and based on his DPR quotation is called, wherein such contractor developer may get first right of refusal for tender based on such DPR. However, Swiss Challenge does not qualify for real advantages meant from ECI, except for assurance of success of the completion of the project.

2.1 Design-Build (DB) The design-build (DB) project delivery system has developed in popularity. The ease of having one party liable for the project development is primary benefit for an owner. In Design-Build (DB), disputes amongst various project participants become internal DB team issues, which do not influence the owner unlike the other system in which owner acting as referee for any disputes among various project participants (or party ultimately to blame). In Design-Build (DB), a single contractor has liability for the design and delivery of a construction project normally on a lump sum fixed price basis. In DB, the owner has a contractual relationship with a single contractor for both design and construction. This single contractor can be an integrated firm or entity, which has an internal design and delivery teams or a consortium of autonomous design and construction firms. The construction performance quality has direct impact of inputs to design teams given by specialised expertise in construction with regards to construction materials, methods and practices [15].

2.2 Construction Management at Risk (CMR) Construction management at risk (CMR) could be a project delivery technique during which a designer (Architect/Engineer) is appointed for project’s design and a construction manager at risk is chosen separately to act as a general construction contractor and additionally design advisor. The risk for construction and consultation in design phase for price & schedule evaluations, characteristic implications of different designs, materials and systems are assumed by the Construction Manager at risk (CMR) at a secured price. Construction Manager (CM) is appointed as general construction contractor throughout construction; this project delivery system is very much just like the standard Design-bid-build (DBB) system. The construction Manager (CM) holds the risk of completion of construction work (with work assign to subcontractors) of the project following completion of the design for either a fixed or negotiated price [2].

2.3 Alliance An alliance is a project delivery technique for construction projects in such the owners work collaboratively with one or more service suppliers like (designers, planners, contractors, construction managers) in single integrated team so as to accomplish a selected project. In such kind all participants work underneath a

[276] Early Contractor Involvement (ECI) as a Construction Project Delivery Method: An Overview contract that aligns their industrial interests with the end result of the project within which they share based on pain-gain share formula. All parties are requested to work underneath full trust & faith, integrity and open book policy. The alliance required forming one integrated team to run the project that consists of members from completely different structure backgrounds; but this team ought to operate as a single body with equal members and take decisions for the best interest of the project only. Therefore, an alliance removes the structure variations and enhances the trust based relationships between members and reciprocally between organizations. In the traditional types of construction contracts include responsibilities and risks allocation for different parties. Those contracts are full of financial and legal consequences in case one party has failed in performing their duties. Sometimes a big risk is being allocated to weak party that is not qualified to deal with such risk which in return will have a bad influence on the project regardless of the contractual compensations. On the other hand, the key factor of alliance contracts is risk sharing. All project risks are being collectively shared and managed by all the participants.

2.4 Swiss Challenge Method Usually the government uses the least cost methodology or the quality and cost based selection methodology for granting these tenders and encourages the general public private partnership for moving the projects. However, without a call for participation from government, a private player will submit a proposal to government for development of an infrastructure project with exclusive intellectual property right and the Original Project Proponent’s proposal is a suo-motu proposal. To avoid allegations of arbitrariness, unfairness and biasness, the foremost common methodology adopted by the govt. in granting approval to such unsolicited proposals is that the Swiss Challenge method [17]. The strategy is associate innovative means of award infrastructure development contracts by the govt. and involves the subsequent process: The government is approached by a private sector entity as an “Originator of Proposal” for a new infrastructure project development or for an existing infrastructure project improvement through “the Original Project Proponent’s proposal”. It is not necessary that such the Original Project Proponent’s proposal have to be a project initiated by the govt. a. Project specifications (technical, business and monetary viability of the project), plan of action, basic contractual terms and a timeframe for completion and implementation of the project are provided by the originator of Proposal to the government. b. If the govt finds the Original Project Proponent’s proposal appropriate and useful, it’s going to talk over directly with the originator of Proposal to bring modifications within the project, as may be needed and approve the Unsolicited Proposal. c. Once the modifications are made, the govt follows the procedure of competitive public bidding, thereby inviting third parties to allow suggestions and improve the initial Unsolicited Proposal. d. The proposal of the chosen bidder (“Selected Bidder”) is then compared with the the Original Project Proponent’s proposal and if the initial Unsolicited Proposal isn’t desirable then the originator of Proposal is given a chance to form his proposal competitive with the proposal of the chosen bidder. e. If the originator of Proposal fails to form his proposal competitive with the proposal of the chosen Bidder, then the chosen Bidder shall be awarded the project. f. But reimbursement is made for the cost incurred by the Original Project Proponent in getting ready the Unsolicited Proposal.

[277] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 3. INTRODUCTION CONCEPT OF EARLY CONTRACTOR INVOLVEMENT (ECI) Early Contractor Involvement (ECI) is effectively a first cousin to the Design Build (DB) contract model and exploits a Contractor’s specialist knowledge regarding construction processes keeping in mind the benefit of design process. The process of ECI starts with a ‘Pre-ECI contract’ stage which involving pre-qualification of contractors and subsequently the procurement of a main contractor. Love et al. (2014) [14] describes that the procurement of a main contractor is based on price as well as qualitative criteria for working in collaborative projects. Therefore, ECI permits contractors to differentiate themselves from competitors based on expertise, capability and experience [6]. Project proceeds into Stage 1 as a main contractor has been appointed. This stage involves the main design and planning work, which is performed by an integrated project team. Stage 1 is usually governed by a professional consultancy agreement where the contractor is reimbursed on an hourly basis and possibly an additional percentage fee [12]. The overall goal of Stage 1 is to develop and agree on a target price for the construction works [13]. When the planning process has resulted in a target price and a construction offer is submitted, progression to Stage 2 can be made. It is desirable that the same contractor performs both Stage 1 and Stage 2 to fully benefit from the established relationships and competence [15]. However, looking on the performance and collaboration throughout Stage one, the construction works is offered to a different party if the client isn’t glad or if the parties cannot agree on a target price [10]. Contractors in ECI are typically selected through a non-price selection method during which the most stress is placed on the potential of the proposed team. The type of contract is decided before being awarded, it is either a standalone “preconstruction” agreement or one contract with 2 distinct stages. In Stage 1 of an ECI contract model, the contractor commences design development up to stipulate design phase or perhaps preliminary design. This design development is undertaken on cost reimbursement basis which inspires innovative design alternatives. Throughout this phase, value engineering and constructability problems is addressed and risks properly known, quenched and dealt out. Stage 1 includes the detailed design submission and pricing for Stage 2 from the contractor and Stage 2 in ECI contracts tends to be a reasonably traditional Design-Build contract. ECI contracts tend to own differing degrees of discretion for the client with relevance the transition from Stage 1 and Stage 2.

4. VERSIONS OF ECI USED IN DIFFERENT COUNTRIES ECI has been successfully utilized in a number of nations across the globe, particularly on projects that are deemed as complicated in relation to stakeholder involvement and delivery timeframe frame [4]. ECI being employed in some countries which adopts a hybrid model wherever the contract starts with a cooperative approach and moves on to a more conventional form of contract like Design and Construct (D&C) [12].

4.1 U.K. Model of ECI ECI was first adopted by the United Kingdom’s Highways Agency in ECI in 2001 and it is now its favoured procurement route. ECI selects contractors by an evaluation of the company’s track record, but not by lowest price bid because there is not yet a design to bid. To build up a target price the owner and contractor then work together on an open-book basis. The contractor is boosted by incentives to design and construct the scheme within this target price on the basis of a pain-gain share formula. The ECI model used by the United Kingdom’s Highways Agency is based on the following two key steps: a. Qualifications-based selection of design and construction parties after completion of feasibility plans and b. Development of open book target pricing system; the project target price later becomes the fixed baseline price. [278] Early Contractor Involvement (ECI) as a Construction Project Delivery Method: An Overview The design and construction parties work through the planning, design, and construction phases with a pain-gain share structure in place that allows savings and losses to be distributed [4].

4.2 Australian Model of ECI The ECI methodology has fruitfully used by the South Australian Department of Transport, Energy and Infrastructure (DTEI). The implemented ECI methodology has two separate phases as following: Phase 1: Design development and Phase 2: Design and construction. Before Phase 1 is started, a contractor or contractor - designer consortium (both will be called “contractor”) are selected on the non-price attributes basis. Although a risk-adjusted maximum price based on a 5% ready design can be part of the tender, this is used mostly to gauge understanding of the works. Phase 1 starts after selection of the contractor and the principles of an alliance contract are followed. The contractor will develop a preliminary design in conjunction with the owner. Compensation for work undertaken in this phase is based on cost reimbursement and is similar to a typical professional services or consultancy contract. When a preliminary design is approximately 70% complete, the second phase is implemented. Phase 2 involves the negotiation of a price to finish the design development and complete the project in regard to construction. If no agreement can be reached on the works price between the owner and the contractor, the owner can terminate the contract and competitively tender the remaining design and the construction. This second phase requires less input by the owner as it uses a general conditions contract and resembles a typical DB contract [4].

4.3 New Zealand Model of ECI In Several infrastructure projects has completed using the ECI model by New Zealand Transport Agency (NZTA) and several more are in various stages of completion. In other fields of construction, the ECI model has been used more extensively. NZTA has prepared the ECI method with three separable portions (SP) as follows: SP1: Research and investigation; SP2: Detailed design preparation, commercial terms, contract price and duration negotiation; SP3: Detailed design and construction works completion. In using this structure, a contractor or consortium is selected by the owner on a non-price basis at the project beginning. However, negotiation of a fixed price is made for each SP before the start of work. The ECI project delivery method not only displays some major differences compared with the traditional methods that have predominantly been used in New Zealand but also differs from an alliance, particularly in the dynamics of moving between the different phases within a single project. For SP1 and SP2, the owner-contractor relationship relies on mutual collaboration, but during execution of construction works in SP3, the owner-contractor relationship is similar to that in a DB [4].

4.4 Netherlands Model of ECI ECI is primarily engaged by the transportation industry in the Netherlands in 2004. The numerous business procurement strategies were introduced by the Netherlands Ministry of Transport in the operation department’s business plan through an ‘interviewing’ approach which has considerable implications in the appeal to contractors in tenders from only cost based criteria to open and functional questions that dealt with the quality and value.

[279] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) The contactors have to elaborate open and functional questions and an award of contract through quality based criteria. To involve construction contractor before the consent of planning decision to which the construction of the project is contracted out was the primary purpose of this method [12].

5. SUCCESS OF ECI IMPLEMENTATION Six important success factors for implementing ECI without disturbing the public procurement directive were recognized by Wondimu et al. (2016) [9]. These findings may offer several valuable insights for public owners in determining significant successful elements in attempt to implement ECI. In general for the betterment of implementation of ECI, these identified success factors plays vital role in formulating effective realistic strategies.

Table 1: ECI Success Factors [9] No. Identified ECI Success Factors 1. Involve contractors early enough 2. Manageable risk transfer to the contractors 3. Project owner’s ability 4. Proper compensation for the contractor’s contribution 5. Qualification of the contractors 6. Trust between the project owner and contractors

6. CONCLUSION If well planned for ensure innovation and strengthened professional relationships, early contractor involvement is a procurement approach that can and result in efficient planning and construction processes. Based on the reported studies, it can be concluded that ECI can be successfully implemented in different forms using combinations of different approaches of project delivery. As public procurement directives are different in different countries, there is scope for future study in the area of project delivery approaches for identification their feasibility and implications in different contract system.

REFERENCES [1] Eadie, R., Graham, M.: Analysing the advantages of early contractor involvement. International Journal of Procurement Management, vol. 7, No. 6, pp. 661–676 (2014). [2] Mahdi, M., Alreshaid, K.: Decision support system for selecting the proper project delivery method using analytical hierarchy process (AHP). International Journal of Procurement Management, pp. 564-572, Elsevier, (2005). [3] Molenar, K. R., Triplett, J. M., Porter, J. C., DeWitt, S. D., Yakowenko, G.: early contractor involvement and target pricing in U.S. and U.K. highways. Journal of the Transportation Research Board, No. 2040, pp. 3-10, Transportation Research Board of the National Academies, Washington (2007). [4] Scheepbouwer, E., Humphries, A. B.: Transition in adopting project delivery method with early contractor involvement. Transportation Research Record: Journal of the Transportation Research Board, No. 2228, pp. 44-50, Transportation Research Board of the National Academies, Washington, (2011). [5] Song, L., Mohamed, Y., Abourizk, S. M.: Early contractor involvement in design and its impact on construction schedule performance. Journal of Management in Engineering, vol. 25, No. 1, ISSN 0742-597X/2009/1-12–20, ASCE, (2009). [6] Eadie, R., Millar, P., McKeown, C. & Ferguson, M.: The feasibility and rationale for using early contractor involvement ECI in the Northern Ireland. In: Proceedings of the 7th International Conference on Innovation in Architecture, Engineering and Construction (AEC). Coleraine: University of Ulster. (2012). [7] Van Valkenburg, M., Lenferink, S., Nijsten, R. and Arts, J.: Early contractor involvement: a new strategy for ‘buying the best’ in infrastructure development in the Netherlands. 3rd International Public Procurement Conference Proceedings, (2008). [8] Walker, D. H. T., Lloyd-Walker, B.: Understanding early contractor involvement (ECI) procurement forms. 28th ARCOM Annual Conference, Edinburgh, vol.2, ISBN: 978-0-9552390-6-9, ARCOM, (2012).

[280] Early Contractor Involvement (ECI) as a Construction Project Delivery Method: An Overview

[9] Wondimu, P. A., Hailemichael, E., Hosseini, A., Lohne, J., Torp, O., Lædre, O.: Success factors for early contractor involvement (ECI) in public infrastructure projects. SBE16 Tallinn and Helsinki Conference; Build Green and Renovate Deep, Energy Procedia 96 (2016), 845 – 854, Elsevier, (2016). [10] Mosey, D.: Early Contractor Involvement in Building Procurement. ISBN 9781444309874, Blackwell, Chichester, (2009). [11] Nichols, M.: Review of Highway Agency’s Major Roads Programme. The Nichols Group, London, (2007). [12] Rahmani, F., Khalfan, M. M. A., Maqsood, T.: The use of early contractor involvement in different countries. RMIT University, (2016). [13] Koncarevic, B.: The performance of early contractor involvement contracts. Proceedings from CIB World Building Congress Construction and Society. Brisbane, (2013). [14] Love, P. E. D., O’Donoghue, D., Davis, P. R. & Smith, J.: Procurement of public sector facilities. Views of early contractor involvement facilities, 32(9), pp. 460-471, (2014). [15] Rahman, M., Alhassan, A.: A contractor’s perception on early contractor involvement. Built Environment Project and Asset Management, 2012, vol. 2, ISS 2, pp. 217-233, Emerald, (2012). [16] Sødal, A. H., Lædre, O., Svalestuen, F., Lohne, J.: Early contractor involvement: advantages and disadvantages for the design team. Proceedings IGLC-22, Oslo, Norway, (2014). [17] Dr. Podil,e V., Rao, N.: Swiss Challenge Method – An Innovative Public Private Partnership Model in India. Asian Journal of Research in Business Economics and Management Vol. 7, No. 7, July 2017, pp. 384-390, (2017).

[281] An Eco-friendly Approach to Municipal Solid Waste Management in Indian Cities

A. Smita Burrewar1 and Anjali Sharma2 1Student, Architecture Department, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Architecture Department, National Institute of Technology Patna, Bihar, India E-mail: [email protected]

ABSTRACT In a developing country like India, waste management continues to be a neglected issue. Garbage produced in most of the Indian cities and towns is not handled competently, despite implementation of the Swachh Bharat Mission. Cities where collection system is operational, wastage is dumped in low-lying areas identified as landfill sites, leading to serious sanitation and environmental issues. With tremendous quantities of rubbish generated yearly, landfills in cities like Delhi, Mumbai and Kolkata are fast running out of space. The cities do not have land for more dump sites. Already full to their capacities long time back, the landfills in these cities are showing indications of overutilization. There have been numerous cases of fire in the dumpsites. The tremendous amounts of trash generated in the Indian cities are reportedly chocking them. By 2047, waste generation in India’s cities will increase five-fold to 260 million tonnes per year. The waste bomb is therefore ticking for India. There is an urgent need to explore, develop and implement an eco-friendly approach to management of municipal solid wastes generated in the Indian cities, with a view to minimize environmental impacts and maximize reuse, recovery and recycling of such waste materials. The objectives of this paper are (1) to have an overview of the best current practises for solid waste management in Indian cities, based on a rigorous literature review; (2) to outline eco-friendly and state-of-the-art mechanism of waste management that can be implemented in Indian cities for an efficient and effective system in place; (3) to explore possibilities of revenue generation from municipal solid wastes such that its management is sustainable. This paper identifies the latest and most efficient measures and practises that enable an eco-friendly approach and state-of-the-art technologies in management of municipal solid wastes. Keywords: Eco-friendly, State-of-the-Art, Municipal Solid Waste, Sustainable, Indian Cities

[282] Resolving Water Scarcity in Bengaluru: An Innovative and Eco-friendly Approach

Kanvi Tiwary1 and Anjali Sharma2 1Urban and Regional Planner, Architecture Department, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Architecture Department, National Institute of Technology Patna, Bihar, India

ABSTRACT Bengaluru, according to experts, will become uninhabitable very soon due to scarcity of water. Once known as the city of lakes Bengaluru is now known cities that are going to run out of water in a few years as per the studies conducted by BBC and World Bank. Even the city’s ground water is contaminated and their levels have declined, which has made even this source of water inadequate and unfit for consumption. Recent estimates of population reveal that Bengaluru already has a population to qualify as the fourth megacity in India after Delhi, Mumbai and Kolkata. Growth of the city’s population at an unprecedented scale is further compounding to the already existing problems. In addition to the problems mentioned above, the city is witnessing a strange combination of issues like flooding and scarcity of water at the same time. Some firm actions are needed to engage with these issues and save the city from this impending disaster that is liable to make Bengaluru unliveable very soon. The objectives of this paper are to 1) establish the water scarcity in Bengaluru by analysing the city’s supply and demand gap; 2) examine the causes of water scarcity in Bengaluru; and 3) propose remedial measures towards solving the problems related to water scarcity in Bengaluru particularly with regard to (i) rejuvenation of the city’s lakes and wetlands, (ii) replenishment of ground water in terms of both quality and levels, (iii) exploring possibilities of alternative sources of water supply that are eco-friendly and cost effective, and (iv) rain water harvesting practices and other similar policy level solutions. Some of these measures have been suggested on the basis of case studies of similar nature. As major findings, this paper has (1) identified innovative and eco-friendly techniques for water supply, sanitation, replenishment of ground water, and rejuvenation of lakes and wetlands in Bengaluru; (2) made comprehensive recommendations for overall improvement of the water shortage and (3) acknowledged that there cannot be any improvement without local people’s participation; (4) recommended exploration and installation of karez technology to augment the water supply of Bengaluru and prevent the city’s water scarcity; and 5) revealed that ICT is inevitable in operation, monitoring, management and control of the lakes and other water-supply related infrastructure. Keywords: Bengaluru, Lakes, Water Scarcity, Eco-Friendly Techniques, Rain Water Harvesting, Karez

[283] Sustainable Urban Forms: A Critical Review of Vastushastra

Naveen Nishant1, Anjali Sharma2, Bijay Kumar Das3 and Fulena Rajak4 1Research Scholar, Architecture Department, National Institute of Technology Patna, Bihar, India 2,3Assistant Professor, Architecture Department, National Institute of Technology Patna, Bihar, India 4Professor, Architecture Department, National Institute of Technology Patna, Bihar, India E-mail: [email protected]

ABSTRACT The modern principles of sustainable urban development, which is rooted in the reports of the Club of Rome and Brundtland Commission, is an old age concept in India which anticipates millennia of existence of cities and towns. Sustainable urban forms were achieved by designing cities and towns based on Vastushastra (traditional Indian system of town planning). Although archaeological findings in this respect are few and far between, ancient religious text provide ample evidence that all ancient Indian settlements were planned on the basis of Vastushastra, which has continued till present times. The objectives of this research paper are (1) to explore the basic concepts of Vastushastra, (2) to review the planning of ancient towns that were designed based on the concepts of Vastu Shastra, (3) to critically analyse the concept of Vastushastra which are eminently sustainable and are relevant even to the present urban development, when applied in a comprehensive manner. This is a first of its kind research on the traditional Indian concept of urban planning and critical analysis of its sustainability and contemporary relevance through a review of a few selected cities that were planned based on the concept of Vastushastra. The major finding of this research based on the critical review of some of the cities planned based on the vastushastra is that this traditional system that has been in existence since millennia of years is immensely suitable for planning to achieve sustainable urban forms even at present. Keywords: Sustainable Urban Forms, Vastushastra, Urban Planning Tradition, India

1. INTRODUCTION The modern principles of sustainable urban development, which is rooted in the reports of the Club of Rome and Brundtland Commission, is an old age concept in India which anticipates millennia of existence of cities and towns. Sustainable urban forms were achieved by designing cities and towns based on Vastushastra (traditional Indian system of town planning). Origin of the now global concept of sustainable development can be traced to the reports of the Club of Rome and Brundtland Commission. However it is an age old concept in India, where cities are expected to exist in terms of thousands of years. Urban forms in ancient Indian cities were highly sustainable. Their sustainability was achieved by designing them on the principles of Vastushastra (traditional Indian system of town planning), which has found continuity till the present times. Vastu Shastra is a Sanskrit term means Architecture. It defines the orientation, proportion, aesthetics, and materials as well as climatological condition principles of delineation and street width in a particular city. The ecological philosophies of the ancient Indian society in Vedic period, guided by several ancient scriptures such as Smritis, Samhitas, Aranyaks, and Puranas and numerous treatises including Manusmruti, Shukra Niti, Agamas, Vastushastra, and Vedas, had profound influence on urban planning in almost all the urban phases in India. Indian cities were variously classified and denominated according to the number and direction of the streets and the arrangement of houses along them [1]. A peculiarity of planning in ancient India, not found anywhere else in the ancient world, is that the planning of villages tally in salient features with that of the cities. A village is a town in miniature, except that while the latter is artificial, the former is natural [1]. [284] Sustainable Urban Forms: A Critical Review of Vastushastra The principles of Vastushastra that were the basis for planning of Indian cities were ecologically oriented. The forms of settlements and towns adopted a holistic and environment-friendly approach in integrating the construction of roads, tanks, houses, temples and water supply and sanitation infrastructure. The Arthashastra (Scripture of Wealth) written around 350 BCE by Kautilya is the most comprehensive testimony of urban planning and environmental practices in ancient India [2]. It advocates adoption of an ecological approach towards planning and urban development and towns to prevent any detrimental impact on the environment ecology [3]. Recently, several scholars have emphasized this traditional system of planning to be an eco-friendly and environmentally aware approach to develop cities. The concept of sustainable development is increasingly being considered akin to the Indian traditional knowledge and system of planning. Vastushastra has at present become increasingly relevant to mankind due to the increased significance of environment because of pollution of air, water and land, resource depletion, climate change, burgeoning population and consequent urban congestion. Through the use of Vastu a connection is established “between functionality, auspiciousness and nature in which one keeps the other alive” [4]. The objectives of this research paper are (1) to explore the basic concepts of Vastushastra, (2) to review the planning of ancient towns that were designed based on the concepts of Vastu Shastra, (3) to critically analyse the concept of Vastushastra which are eminently sustainable and are relevant even to the present urban development, when applied in a comprehensive manner.

2. MATERIALS AND METHODS This research paper is based on a qualitative research. For conducting this research paper a large numbers of books, journals, newspapers, magazines, TV programmes, conference proceedings, etc. are used, apart from internet based sources, working papers as well as personal interview and reconnaissance survey which also play an important role in preparing this particular research paper in an elaborate way. The towns reviewed are those that were the hallmark of the urban phase in which they existed and at the same time represent a chronology and planning over 5000 years based on the philosophies of Vastushastras. In their planning reveal a sustainable approach to urban planning. The details of the cities that have been studied are given in Table 1.

Table 1: Cities of Different Urban Phases in India for Case Study Whether Phase City Continuously Location Sources of Information Inhabited? IVC Dholavira No Near Indus River Bisht, 1997, 1999; McIntosh, 2008; Douglas, 2013 Gangetic Sisupalgarh No Near Ganga River Mohanty, Smith, Matney, Donkin, & Greene, 2007; Ghosh, 1989; Ray, 2007; Schlingloff, 2014, Dravidian Warangal Yes Telangana State Michell, 1992; Nagaich, 2017 Islamic Fatehpur Sikri No Uttar Pradesh Rezavi, 2011; Asher, 1992; Harris, 2015 Havell, State 1913; Petersen, 1996 Post Jaipur Yes North India Mitter, 1986; Das & Rampuria, 2015; Dutt, 1925; Independent Havell, 1913 Chandigarh Yes North India R. Patra, 2009; Crabtree, 2015 Present/ Amravati Being Andhra Pradesh Andhra Pradesh Capital Region Development Upcoming established State Authotity, 2019

3. RESULTS The basic concepts of vastushastra and the case studies of the towns planned on the principles of vastushastra are detailed below: [285] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

3.1 Basic Concepts of Vastushastra Cities were representations of the cosmos, and were the domain of the sacred. Their planning was therefore based on cosmological principles laid down in the Vastushastra, which translates to “the science of places where immortals and mortals live” and is a Vedanga, a branch of Sthapatya Veda–a part of Yajur Veda [5]. The ancient Indian cities reveal “high level meaning” through their built environments, describing “cosmological and supernatural symbolism” implied in their layouts. Buildings and cities were “cosmograms,” or deliberate physical models of the cosmos. the cosmological significance of settlements is highlighted by Smith (2007) through four fundamental philosophies: “(1) there is a parallel between the workings of heavens and life on earth; (2) the basic link between earth and the cosmos is the axis mundi; (3) the cosmos are laid out in four cardinal directions, and human constructions should imitate this; and (4) divination and augury are needed to identify and sanctify sacred space on earth” (M. E. Smith, 2007). Uniquely Hindu because of its metaphysical basis, the earliest Vastu principles had been framed in accordance with the rays of the sun at different times of the day [5]; clear and extensive evidence of a planned, and orderly life for all the people in these settlements in ancient India aimed at promoting their health and well-being [6]. The system of planning comprised of ten steps as described below: Examination of Soil (Bhu-pariksha): Examination of soil was done to assess its fitness on the basis of several factors. The preliminary foregoing indicators of disqualification are “impurity, insanitation, sterility, insolidity, hollowness, and irregularity of sites or plots which would affect the shape of buildings,” demarcation and “establishment of rectilinear streets and the stability of structures erected on them” [6]p. 52. Only when the soil was found satisfactory in all aspects, the site was selected for establishing a village, industry, town, fort etc. [5]. Site-Selection (Bhumismgraha): Selection of site for a village or a town was carefully done particularly with regard to its natural setting, so that it could best be turned into fortifications. Water seems to be the most important criteria for site selection, since the site considered most auspicious for a town was the curvilinear bank of a river or the confluence of two rivers, and along sea-shores, or near a lake or a big tank since ablution for Hindus as a religious rite, was indispensable and to provide unfailing water-supply [6], [7]. Kaushambi, the capital of Vatsa located at the confluence of Ganga and Yamuna. Pataliputra was located at the confluence of five rivers [8]. The most favourable sites were those surrounded by “milky trees, full of fruits and flowers,” with a lower eastern side to receive rising sun’s rays on the front doors, as against that located on the Western side of a mountain [6]. Determination of Directions (Dikpariccheda): Determination of directions was an essential first step since the cardinal directions hold a particular significance in Vastushastra [6]. The eight principal directions variously associated with a deity and a particular function explain the principles of orientation in Vastushastra [5]. “There was a network of streets running mostly in the cardinal directions and cutting one another at right angles. The houses were flanked on both sides of streets and lanes. These streets and lanes were generally straight and divided the township in block and sub-blocks showing a chessboard pattern of the plan. When the longest arm is aligned in the East and West direction then it is called as Mahakala or Vamana. While ring roads planned surrounding the whole city or town then it is called as Manglavithi [9]. The main road should be eight dandas wide and other roads should be four dandas wide. The major streets did not approached upto the houses and the doorways of the houses did not open in the major streets. So the lanes were made to access the facilities for the movement upto their houses. The width of the lanes were less than the streets. The vehicular activities were restricted in the lanes. Division of the Grounds into Squares (Padavinyasa): The ground was divided into squares by the streets, which were arranged and planted according to the rectangular chess-board system. This system, originating from agriculture and farming, is considered the most natural method of street planning and the simplest and the most convenient for building block [6], based on a system of measurement prescribed in Manasara with ‘Danda’ and ‘Hasta’ as the units of measurement [4]. [286] Site - Selection (bhumismgraha) – Selection of site for a village or a town was carefully done particularly with regard to its natural setting, so that it could best be turned into fortifications. Water seems to be the most important criteria for site selection, since the site considered most auspicious for a town was the curvilinear bank of a river or the confluence of two rivers, and along sea-shores, or near a lake or a big tank since ablution for Hindus as a religious rite, was indispensable and to provide unfailing water-supply [6], [7]. Kaushambi, the capital of Vatsa located at the confluence of Ganga and Yamuna. Pataliputra was located at the confluence of five rivers [8]. The most favourable sites were those surrounded by “milky trees, full of fruits and flowers,” with a lower eastern side to receive rising sun’s rays on the front doors, as against that located on the Western side of a mountain [6]. Determination of directions (dikpariccheda) – Determination of directions was an essential first step since the cardinal directions hold a particular significance in Vastushastra [6]. The eight principal directions variously associated with a deity and a particular function explain the principles of orientation in Vastushastra [5]. “There was a network of streets running mostly in the cardinal directions and cutting one another at right angles. The houses were flanked on both sides of streets and lanes. These streets and lanes were generally straight and divided the township in block and sub-blocks showing a chessboard pattern of the plan. When the longest arm is aligned in the East and West direction then it is called as Mahakala or Vamana. While ring roads planned surrounding the whole city or town then it is called as Manglavithi [9]. The main road should be eight dandas wide and other roads should be four dandas wide. The major streets did not approached upto the houses and the doorways of the houses did not open in the major streets. So the lanes were made to access the facilities for the movement upto their houses. The width of the lanes were less than the streets. The vehicular activities were restricted in the lanes. Division of the grounds into squares (padavinyasa) – The ground was divided into squares by the streets, which were arranged and planted according to the rectangular chess-board system. This system, originating from agriculture and farming, isSustainable considered Urban the Forms: most Anatural Critical Reviewmethod of ofVastushastra street planning and the simplest and the most convenient for building block [6], based on a system of measurement prescribed in Manasara with ‘Danda’ andVastu ‘Hasta’ Purush as Mandala the units ofis ameasurement highly advanced [4]. term which gives information about any supernatural forces of Vastua cosmic Purush man Mandala that resides is a inhighly a cosmic advanced diagram. term Hencewhich itgives is also information called as abouta magical any supernaturaldiagram. The forces mode of of a cosmicdivision man into that padas resides is by in drawing a cosmic two diagram. to thirty-three Hence it rectilinearis also called parallel as a magical lines and diagram. as many The transverse mode of divisionparallel intolines. padas These is thierty-twoby drawing schemestwo to thirty of -divisionthree rectilinear are distinguished parallel lines by andas many as many different transverse names parallel according lines. toThese the thiertynumber-two of squaresschemes into of divisionwhich the are whole distinguished area is partitioned by as many out. different And their names names according in serial orderto the arenumber Sakala of, squaresPeechaka into, Pitha which, Mahapitha the whole, etc.,area endingis partitioned with thirty-second out. And their Indrakanta names in [6].serial order are Sakala, Peechaka, Pitha, Mahapitha, etc., ending with thirty-second Indrakanta [6].

FigureFig. 1: Different1 Different Mandalas mandalas from Left: from Paramasaayika, left: Paramasaayika, Pitah, Sakala, Pitah, Pechaka, Sakala, Mahapitah, Pechaka, Manduka, Mahapitah, Chandita Manduka, Mandala Chandita mandala The offeringsOfferings ( balikarmavidhana(Balikarmavidhana) – ):“The “The laying laying out out of of village villagess is is treatedtreated inin thethe Silpa Sastras as thethe preparation of of sacrificial sacrificial ground. ground.”” The The plan planss of ofvillages, villages, towns towns and and cities cities along along with with their their denominations denominations were identicalwere identical to the geometricalto the geometrical figures drawnfigures on drawn the sacrificial on the sacrificial altars [6] .altars [6]. The planning of villages and towns (gramavinyasa, nagaravinyasa) – The planning of villages and towns was doneThe Planningonce the principal of Villages streets and were Towns laid out. (Gramavinyasa, The entire city wasNagaravinyasa then divided): into The grama planning (wards), of villages which resembledand towns the was shape done of once the wholethe principal city on streetsa smaller were scale. laid However, out. The allentire the citygramas was were then notdivided laid outinto with grama the same(wards), pattern which but resembledwas determined the shapeby the ofrequirements the whole ofcity the on profession a smaller of scale. the ward However, residents. all All the the gramas wards werewere not dividedlaid out into with th ethe same same number pattern of building but was plots; determined neither were by the buildings,requirements roads of and the lanes profession planted ofon thethe sameward residents.plan. All Allthe thevarious wards types were of not village divided-plans into were the samesometimes number adopted, of building even plots;in a singleneither town. were Thethe rectangularbuildings, roads and square and lanes shapes planted were most on the favoured same plan.because All theythe various facilitated types planning of village-plans of sites, buildings were sometimes and their orientationadopted, even whereas in athe single circular, town. triangular, The rectangular multi-angular, and orsquare irregular shapes shapes were were most denounced favoured [6] . because they facilitatedIndian planning cities of were sites, variously buildings classified and their and orientation denominated whereas according the circular,to the number triangular, and direction multi-angular, of the streetsor irregular and theshapes arrangement were denounced of houses [6]. along them [1]. The greatest city has seventeen thoroughfares both lengthwise and breadthwise. A capital city had three royal highways in the east-west direction and three north- south,Indian dividingcities were the variouslycity into 16classified sectors, andeach denominatedsector having accordinga specific typeto the of numberland-use, and depending direction upon of thethe professionstreets and or the caste arrangement of its inhabitants of houses [10] along. The classificationthem [1]. The of greatest villages cityand hastowns seventeen according thoroughfares to the number both and directionlengthwise of theand streets breadthwise. are given A below: capital city had three royal highways in the east-west direction and three a.north-south, Dandaka dividing(the staff) the followed city into a ribbon16 sectors, development each sector along having principal a specificstreet and type had of five land-use, long parallel depending street uponrunning the profession East-West or with caste three of transverseits inhabitants streets [10]. intersecting The classification them at the ofmiddle villages and and two townsextremes according [11]. to the number and direction of the streets are given below: Dandaka (the staff) followed a ribbon development along principal street and had five long parallel street running East-West with three transverse streets intersecting them at the middle and two extremes [11]. Sarvatobhadra (the quadrangular grid) is a larger village or town constructed on a square site with concentric streets. [12]. Swastika (equilateral cross or pinwheel or cruciform) plan resembles the pattern of a swastika with two main streets that ran in the middle East-West and North-South and used for defence of the four gateways [11], as at Warangal. Prastara (conch) plan is square or oblong in form and divided into four, nine or 16 major parts by appropriate number of streets [12], the sizes of the sites were determined by the capacity. Chaturmukha (four-faced) pattern was applicable to all types of settlements from largest city to the smallest village and had four main streets. Padmaka (lotus) pattern resembles the petals of lotus radiating outwards from the center.

[287] b. Sarvatobhadra (the quadrangular grid) is a larger village or town constructed on a square site with concentricb. Sarvatobhadra streets. [12] (the. quadrangular grid) is a larger village or town constructed on a square site with c. Swastikaconcentric (equilateral streets. cross[12]. or pinwheel or cruciform) plan resembles the pattern of a swastika with two mainc. Swastikastreets that (equilateral ran in the cross middle or pinwheel East-West or cruciform)and North plan-South resembles and used the forpattern defence of a ofswastika the four with gateways two [11], mainas at Warangal.streets that ran in the middle East-West and North-South and used for defence of the four gateways d. Prastara[11] , (conch)as at Warangal. plan is square or oblong in form and divided into four, nine or 16 major parts by appropriated. Prastara number (conch) of planstreets is [12]square, the or sizes oblong of thein formsites wereand divided determined into byfour, the nine capacity. or 16 major parts by e. Chaturmukhaappropriate (fournumber-faced) of streets pattern [12] ,was the sizesapplicable of the sites to wereall types determined of settlements by the capacity. from largest city to the e. Chaturmukha (four-faced) pattern was applicable to all types of settlements from largest city to the smallestsmallest village village and andhad hadfour four main main streets. streets. nd f. Padmakaf. Padmaka (lotus (lotus) patterne-Book:) pattern resembles 2 resemblesNational the Conference the petals petals of on of lotus Recent lotus radiating radiating Advances outwards in Civil Engineering from from the the (RACE-II)center. center.

(a) (a) (b) (b) (c) (c) (d) (d) (e) (e) Figure (a2 Street) patterns based (b) on Vastushastra (a) Dandaka(c) , (b) Sarvatobhadra (d) , (c) Swastika , (d)(e) Prastara , (e) FigureChaturmukha 2 Street patterns [6]Fig.. 2:based Street on PatternsVastushastra based (a) on Dandaka Vastushastra, (b) Sarvatobhadra (a) Dandaka, (b), (c) Sarvatobhadra Swastika, (d) ,Prastara , (e) Chaturmukha [6]. (c) Swastika, (d) Prastara, (e) Chaturmukha [6]

(a) (b) (c) (d) (e) (f) Figure 3 Variants of Padmaka (a)-(b), and Nandyavarta (c)-(e), (f) Karmukha [6] (a)(a) (b)(b) (c) (c) (d) (d) (e) (e) (f) (f) Figureg. 3 VariantsNandyavarta of Padmaka (quadrangular (a)-(b), concentric and Nandyavarta) was used for(c) -construction(e), (f) Karmukha of towns [6] and not for villages comprised Fig. 3: Variants of Padmaka (a)-(b), and Nandyavarta (c)-(e), (f) Karmukha [6] 49 square, 64 square and 81 square mandalas in its layouts [10]. g. NandyavartaNandyavartah. Karmuka (quadrangular( (quadrangularbow) depict a radio concentricconcentric)-concentric) was was arrangement used used for for construction construction of radial streets of of townsconverging towns and and notat notthe for centerfor villages villages [10] .comprised comprised 4949 square,Buildings square, 64 64and square square their andanddifferent 8181 square square storeys mandalas mandalas (bhumividhana in itsin itslayouts) layouts – The [10] height [10].. of all the buildings constructed on the h. Karmukasame street (bow was) usuallydepict athe radio same-concentric for an all- roundarrangement uniformity, of rad forial only streets a particular converging class atwas the allowed center residence[10]. BuildingsKarmukain the and same (bow) their street depict different (Kulke a radio-concentric& storeysRothermund (bhumividhana, 2002 arrangement). Buildings) – The andof radialheight their storeys streetsof all weretheconverging buildings specified at constructedaccording the center to onthe[10]. the same street widthwas usuallyto achieve the a sameproper for correlation an all-round between uniformity, the width forof street,only athe particular height of classbuildings was alallowedong them, residence and Buildings and Their Different Storeys (Bhumividhana): The height of all the buildings constructed in thethe same rank street of occupant. (Kulke The& Rothermund imperial palaces, 2002 were). Buildingsraised to eleven and their storeys; storeys the buildings were specified of Brahmanas according to nine to the on the same street was usually the same for an all-round uniformity, for only a particular class was allowed street storeys;width to those achieve of the a ordinaryproper correlation kings to seven between storeys; the those width of satrapsof street, (samanta the height) to five of buildingsstoreys; Vaisyas along andthem, the and theresidence ranksoldier of occupant.classin the had same fourThe storeyedimperialstreet (Kulkebuilding palaces & and wereRothermund, Sudras raised could to buildeleven2002). their storeys; Buildings houses the only andbuildings up theirto three ofstoreys storeysBrahmanas werehigh. Thetospecified nine houses of Brahmans were chatursala (sala=long structures of the same span only) – occupied the four sides of a storeys;according those to of thethe streetordinary width kings to to achieve seven storeys; a proper those correlation of satraps between(samanta the) to fivewidth storeys; of street, Vaisyas the andheight the of buildingsquadrangle along with them, an open and space the in rank the centre;of occupant. those of theThe Kshatriyas imperial were palaces trisala were (constructed raised toon eleventhree sides storeys; of a the soldierquadrangle); class had fourthat ofstoreyed vaisyas buildingdvisala (constructed and Sudras on could two sides); build and their Sudras houses ekasala only (constructedup to three onstoreys just one hig sideh. The housesbuildingsof of a Brahmansquadrangle). of Brahmanas were The chatursalaplane to ninefaçade (storeys; salathus =longobtained those structures from of thesuch of ordinary athe construction same kingsspan would only)to seven form– occupied astoreys; wall onthe boththose four sides sides of ofsatraps of a quadrangle(samantathe street with) to or five ancould open storeys; be spaceused Vaisyas for in decorationthe centre;and the or those mural soldier of [6] the .class Kshatriyas had four were storeyed trisala building (constructed and onSudras three couldsides of build a quadrangle);theirConstruction houses that only of of vaup gatewaysisyas to three dvisala (gopuravidhana storeys (constructed high. )The –on Construction twohouses sides); of of Brahmansand gateways Sudras waswere ekasala an chatursala integral (constructed part (sala of theon=long justextensive onestructures side ofof a thequadrangle).fortifications, same span Thecomprising only)–occupied plane façade embattled thus the walls obtained four and sides deep from of trenches asuch quadrangle a for construction defence. with The an would citiesopen formwere space aadvanced wall in the on centre;v bothersions sides thoseof of of thethe street theKshatriyas earlyor could Aryan were be villages;used trisala for they(constructeddecoration were all or walled onmural three cities, [6] sides. rectangular of a quadrangle); or square, usually that of with vaisyas four gatedvisalas, one (constructed in the Constructionon twocentre sides); of eachof gatewaysand side. Sudras A fort (gopuravidhana withekasala three (constructedroads) each – Construction in theon east just-west oneof gatewaysand side north of -a southwas quadrangle). andirection integral had Thepart altogether planeof the façadetwelveextensive thus fortifications,gates approached comprising by both embattled land and walls water, and some deep of whichtrenches were for kept defence. secret. The cities were advanced versions of obtainedConstruction from suchof temples a construction (mandapavidhana would) –form Since a thewall central on bothspace insides a city of linked the streetthe heaven or could and the be earth, used for thedecoration early Aryan or villages;mural [6]. they were all walled cities, rectangular or square, usually with four gates, one in the centreit of was each usually side. eitherA fort openwith orthree occupied roads eachby a intemple the east(Reddy-west & and Almoori, north- south2012) directionof its tutelary had altogetherdeity with twelveits Constructionspacious mandapa of Gateways or the council (Gopuravidhana-trees or pavilions located): Construction at the crossing of gateways of two main was roads an integralwith a pedestal part of the gates approachedraised round byit orboth comprised land and a water,common some tank of [6] which, or was were reserved kept secret. for the ruler (Mitter, 1986) or formed an Constructionextensiveensemble fortifications, ofof templesseveral religious, (comprisingmandapavidhana royal embattledand public) – Since buildingswalls the and central (such deep as spacetrenches the shrine, in a for city the defence. linked palace, the Thethe heaven court cities, the wereand council, the advanced earth, it versionswasthe usually ministers of theeither quartersearly open Aryan and or theoccupied villages; army commanders, bythey a templewere the all (Reddy treasurywalled & andcities, Almoori, other rectangular important 2012) ofbuildings), or its square, tutelary that usually bedeitycam ewitwith theh itsfour spaciousgates, onemandapa in the orcentre the council of each-trees side. or A pavilionsfort with threelocated roads at the each crossing in the ofeast-west two main and roads north-south with a pedestal direction raisedhad altogetherround it or twelvecomprised gates a approachedcommon tank by [6] both, or landwas andreserved water, for some the ruler of which (Mitter, were 1986) kept or secret. formed an ensemble of several religious, royal and public buildings (such as the shrine, the palace, the court, the council, theConstruction ministers quarters of andTemples the army (Mandapavidhana commanders, the treasury): Since and the other central important space buildings),in a city linked that be thecam heavene the and the earth, it was usually either open or occupied by a temple (Reddy & Almoori, 2012) of its tutelary deity with its spacious mandapa or the council-trees or pavilions located at the crossing of two main roads with a pedestal raised round it or comprised a common tank [6], or was reserved for the ruler (Mitter, 1986) or formed an ensemble of several religious, royal and public buildings (such as the shrine, the

[288] Sustainable Urban Forms: A Critical Review of Vastushastra palace, the court, the council, the ministers quarters and the army commanders, the treasury and other important buildings), that became the hub of activities or the public square (sabha), which, according to Dutt (1925), was a remarkably distinctive characteristic of the Aryan town planning and a reflection of community living. Construction of Royal Palaces (Rajavesmavidhana): The royal palace was built in a capital city and occupiedhub of activitiesa central or position the public within square the (sabha), city and which, was usuallyaccording located to Dutt within (1925), a wasforested a remarkably park, with distinctive fountains andcharacteristic fish ponds of[6]. the Aryan town planning and a reflection of community living. Construction of royal palaces (rajavesmavidhana) – The royal palace was built in a capital city and occupied 3.2a centralRevie positionw of Twithinowns the P lannedcity and was based usually on located Vastushastra within a forested park, with fountains and fish ponds [6]. The case studies have been conducted by selecting one city in each of the urban phases in India. A review of these3.2 citiesReview has revealed of towns that planned vastushastra based on has Vastushastra been the guiding: factor for planning of cities throughout history. The details of each of the selected cities are given below: The case studies have been conducted by selecting one city in each of the urban phases in India. A review of Dholavira:these cities Dholavira has revealed lying that inside vastushastra the Rann has ofbeen Kutchh, the guiding is one factor of the for largest planning cities of within cities throughoutthe Indus-Saraswati history. realmThe ofdetails “diverse of each and of thevaried selected ecologies” cities are [13]. given This below: ruined city is enclosed in an area of about 48 ha. It is quadrangularDholavira - inDholavira shape andlying was inside occupied the Rann from of Kutchh,2650 BCE, is one declined of the largest gradually cities after within around the Indus 2100-Saraswati BCE and wasrealm reoccupied of “diverse until and 1450 varied BCE. ecologies” Dholavira [13] had. This massive ruined brickcity is walls enclosed surrounding in an area it ofas aboutwell as48 its ha. separate It is parts,quadrangular built on inbrick shape revetment and was occupiedas foundation from 2650 platforms BCE, declined demarcating gradually the after main around areas 2100 of BCEthe settlementand was [14].reoccupied The elaborate until 1450 town BCE. planning Dholavira of had Dholavira massive brickconsciously walls surrounding uses specific it as wellproportions as its separate for its parts enclosures, built accordingon brick torevetment Michel Danino,as foundation 2008 platforms based on demarcating angulas, dhanus/dandas the main areas of[15]. the settlement [14]. The elaborate town planning of Dholavira consciously uses specific proportions for its enclosures according to Michel Danino, 2008 based on angulas, dhanus/dandas [15].

Figure 4 Planning of Dholavira (Bisht, 1997) Figure 5 Planning of Sisupalgarh [19] Fig. 4: Planning of Dholavira (Bisht, 1997) Fig. 5: Planning of Sisupalgarh [19] Dholavira had a unique threefold division – a bipartite citadel comprising a huge castle and a bailey, a middle Dholaviratown along had with a unique a large threefold esplanade division–a (ceremonial bipartite ground, citadel paved forcomprising convenience a huge of holding castle andevents), a bailey, and a a lower middle towntown along comprising with a alarge series esplanade of reservoirs (ceremonial [16], [17]. Theground, strictly paved rectilinear for convenience streets are aligned of holding slightly events),Northwest and – a Southwest. “Dholavira had sixteen reservoirs of varying dimensions, within the city walls on three sides along lower town comprising a series of reservoirs [16], [17]. The strictly rectilinear streets are aligned slightly the northern, western and southern and within the citadel covering approximately 36% of the total walled area Northwest–Southwest.which stored was appropriated “Dholavira alone had for sixteen the storag reservoirse of the ofwater varying harnessed dimensions, from two within streams the Manhar city walls and on threeMansar sides”[18] along. the northern, western and southern and within the citadel covering approximately 36% of theSisupalgarh total walled / Kalinganagara area which stored– Sisupalgarh was appropriated, a mid-first millennium alone for BCEthe storage city had of a thesquare water plan harnessed (Chaturasra from) twoand streams pillars Manharfound in theand centre Mansar”[18]. of the town reveal that a substantial “palace precinct” existed in the centre [20]). Massive fortifications comprising earthen rampart crowned with parapets along with moat [6] have been found Sisupalgarh/at Sisupalgarh ..Kalinganagara A rampart 4.4 km: Sisupalgarh,long [21] and 9a m mid-first high [20] ,millennium made of laterite BCE blocks city hashad been a foundsquare [22] plan. (ChaturasraMoat, ditch) andor natural pillars water found barriers in the was centre an important of the town aspect reveal of defence that afor substantial the fort or the“palace city [23] precinct”. Sometimes, existed the moats also served as a source of water for the town.[289] Sisupalgarh is circumscribed by the water streamlet called the Gangua [6], [23]. Excavations at Sisupalgarh indicate presence of eight gateways [21]. The square plan of Sisupalgarh indicate a parallel layout of major streets from gateway to gateway [24]. Warangal –. Archaeological studies have revealed existence of circular cities, especially in the South Indian phase of urbanization such as Dhar and Warangal. The early Medieval (Hindu) cities were built as fortresses, mostly located in the valley floors surrounded by hills or on top of a hill. Warangal (Figure 2) occupied an extensive plain with a distinctive granite boulder known as ekashila (single rock) [25], and was built by Kakatiya rulers as their capital city in the twelfth century with a circular (golavrtta) shape, indicating cosmic significance. The circular plan manifested in “a sequence of three concentric circuits of fortifications” of 1.2 km, 2.4 km and 12.5 km diameters comprising the fort, the residential quarters and the agricultural areas respectively. The innermost wall is made of stone and lined on the outside with “massive granite blocks, fitted e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) in the centre [20]). Massive fortifications comprising earthen rampart crowned with parapets along with moat [6] have been found at Sisupalgarh. A rampart 4.4 km long [21] and 9 m high [20], made of laterite blocks has been found [22]. Moat, ditch or natural water barriers was an important aspect of defence for the fort or the city [23]. Sometimes, the moats also served as a source of water for the town. Sisupalgarh is circumscribed by the water streamlet called the Gangua [6], [23]. Excavations at Sisupalgarh indicate presence of eight gateways [21]. The square plan of Sisupalgarh indicate a parallel layout of major streets from gateway to gateway [24]. Warangal: Archaeological studies have revealed existence of circular cities, especially in the South Indian phase of urbanization such as Dhar and Warangal. The early Medieval (Hindu) cities were built as fortresses, mostly located in the valley floors surrounded by hills or on top of a hill. Warangal (Figure 2) occupied an extensive plain with a distinctive granite boulder known as ekashila (single rock) [25], and was built by Kakatiya rulers as their capital city in the twelfth century with a circular (golavrtta) shape, indicating cosmic significance. The circular plan manifested in “a sequence of three concentric circuits of fortifications” of 1.2 km, 2.4 km and 12.5 km diameters comprising the fort, the residential quarters and the agricultural areas respectively. The innermost wall is made of stone and lined on the outside with “massive granite blocks, fitted in irregular fashion, without any mortar, to a height of 6m, with 45 bastions altogether,” while the inside has lining of rammed earth supported by stepped blocks that lead to the broad pathway on top of the walls. A moat is provided on the outside. The intermediate wall is 10 m high,in irregular with semi-circularfashion, without buttresses, any mortar, and to aencircled height of by6m, a with deep 45 moat.bastions The altogether,” third circuit while of the walls inside rise has upto 5 m,lining without of rammed any buttress. earth supported Gateways by stepped were blocksprovided that leadin cardinal to the broad direction pathway in on all top the of threethe wall ringss. A ofmoat walls, alignedis provided to each on theother. outside. The Thesouth-east intermediate quadrant wall is 10of mthe high, fort with has semi a large-circular lake buttresses, which is and overlooked encircled by by a the ekshiladeep hill,moat. comprising The third circuit a small of templewalls rise at uptothe top5 m, of without this granite any buttress. outcrop, Gateways rises abruptly were provided from inthe cardinal lake. The citydirection had a radial in all thesystem three ofrings roadways of walls, withaligned eight to each roads other. converging The south -toeast the quadrant inner fort.of the The fort gatewayshas a large openedlake in differentwhich is directionsoverlooked according by the ekshila to rotational hill, comprising symmetry. a small The temple scheme at theof movementtop of this granitethrough outcrop, the innermost rises abruptly from the lake. The city had a radial system of roadways with eight roads converging to the inner fort. andThe intermediate gateways opened circuits in ofdifferent Warangal’s directions fortifications according tocreates rotational a swastika symmetry. pattern, The scheme which ofis movementimagined as spinningthrough to the the innermost right in clockwiseand intermediate direction. circuits The of specialtyWarangal's of fortifications swastika plan creates was a formationswastika pattern, used forwhich defence is of theimagined four gateways as spinning [11], to the right in clockwise direction. The specialty of swastika plan was formation used for defence of the four gateways [11],

Figure 6 Warangal, with three concentric rings of fortifications, and the inner city (adapted from [25]) Fig. 6: Warangal, with Three Concentric Rings of Fortifications and the Inner City (Adapted from [25]) The theoretical model of Warangal indicates conscious planning on well-established traditions, as detailed out in Thethe theoretical religious texts,model comprising of Warangal the circular indicates shape conscious and the swastikaplanning pattern on well-established – deemed fit for traditions,habitation ofas kings detailed out andin the also religious serves as texts,a cosmogram comprising [25]. the circular shape and the swastika pattern–deemed fit for habitation of kingsFatehpur and Sikrialso serves- Fatehpur as aSikri cosmogram (1569), built [25]. on the broad top of a rocky ridge of the Vindhyan hill ranges as an irregular quadrangle, had high fortification on three side and Kol Lake on the fourth (north-west) [26]–[28]. Shahjahanabad (1639) was built on a bluff along Yamuna[290] River in the northern part of the Delhi triangle [29]. Fatehpur Sikri represents a fusion of the Islamic urban design concepts with the traditional Indian system of town-planning, as manifested in several Islamic cities, most notably in Fatehpur Sikri (Error! Reference source not found.), designed by Tuhir Das [30].

Figure 7 Plan of Fatehpur Sikri (adapted from Havell, 1913) Jaipur - Sensitivity to the natural surroundings and resources were the key factors in determining the urban form of Jaipur, which is obvious in the plan of the city (Figure 4) [4], the present capital of Rajasthan founded in 1727 by Sawai Jai Singh and laid out as prastara by Vidyadhar Bhattacharya [6]. Defended by the Nahargarh Fort, and in accordance with the system of vastupurusa-mandala laid down in the Shilpa shastras, the main avenue laid out from east to west is cut across by two major streets delineated north to south and divide Jaipur into nine parts [26], [31]. This fairly regular layout of the streets and their orientation is based on the prevalent wind direction and solar and lunar paths to ensure purification of the streets. Dimensions and form of the Mandala are determined on the basis of natural features such as hills, forests and water bodies existing at the site in irregular fashion, without any mortar, to a height of 6m, with 45 bastions altogether,” while the inside has lining of rammed earth supported by stepped blocks that lead to the broad pathway on top of the walls. A moat is provided on the outside. The intermediate wall is 10 m high, with semi-circular buttresses, and encircled by a deep moat. The third circuit of walls rise upto 5 m, without any buttress. Gateways were provided in cardinal direction in all the three rings of walls, aligned to each other. The south-east quadrant of the fort has a large lake which is overlooked by the ekshila hill, comprising a small temple at the top of this granite outcrop, rises abruptly from the lake. The city had a radial system of roadways with eight roads converging to the inner fort. The gateways opened in different directions according to rotational symmetry. The scheme of movement through the innermost and intermediate circuits of Warangal's fortifications creates a swastika pattern, which is imagined as spinning to the right in clockwise direction. The specialty of swastika plan was formation used for defence of the four gateways [11],

Figure 6 Warangal, withSustainable three concentric Urban Forms: rings of A fortifications,Critical Review and of Vastushastra the inner city (adapted from [25]) FatehpurThe Sikri: theoretical Fatehpur model of Sikri Warangal (1569), indicates built conscious on the planningbroad top on well of a-established rocky ridge traditions, of the as Vindhyan detailed out hillin ranges the religious texts, comprising the circular shape and the swastika pattern – deemed fit for habitation of kings as an irregularand also servesquadrangle, as a cosmogram had high [25]. fortification on three side and Kol Lake on the fourth (north-west) [26]–[28].Fatehpur Shahjahanabad Sikri - Fatehpur (1639) Sikri (1569),was built built on on athe bluff broad along top of Yamunaa rocky ridge River of the in Vindhyan the northern hill ranges part as of an the Delhi triangle irregular[29]. Fatehpur quadrang le,Sikri had representshigh fortification a fusion on three of sidethe andIslamic Kol Lakeurban on designthe fourth concepts (north-west) with [26] the–[28] traditional. Shahjahanabad (1639) was built on a bluff along Yamuna River in the northern part of the Delhi triangle [29]. Indian systemFatehpur ofSikri town-planning, represents a fusion as ofmanifested the Islamic urbanin several design conceptsIslamic withcities, the mosttraditional notably Indian in system Fatehpur of Sikri (Error! townReference-planning, sourceas manifested not infound. several), Islamicdesigned cities, by most Tuhir nota Dasbly [30].in Fatehpur Sikri (Error! Reference source not found.), designed by Tuhir Das [30].

Figure 7 Plan of Fatehpur Sikri (adapted from Havell, 1913) Jaipur - Sensitivity toFig. the 7: natural Plan surroundingsof Fatehpur andSikri resources (Adapted were from the keyHavell, factors 1913) in determining the urban form of Jaipur, which is obvious in the plan of the city (Figure 4) [4], the present capital of Rajasthan founded in Jaipur:1727 Sensitivity by Sawai toJai theSingh natural and laid surroundingsout as prastara byand Vidyadhar resources Bhattacharya were the [6] . keyDefended factors by thein Nahargarhdetermining the urban formFort, ofand Jaipur, in accordance which withis obvious the system in theof vastupurusa plan of the-mandala city (Figure laid down 4) [4],in the the Shilpa present shastras, capital the ofmain Rajasthan foundedavenue in 1727 laid outby fromSawai east Jai to westSingh is cutand across laid by out two as major prastara streets bydelineated Vidyadhar north to Bhattacharya south and divide [6]. Jaipur Defended by the Nahargarhinto nine parts Fort, [26], [31]and. This in accordancefairly regular layout with of the the streetssystem and of their vastupurusa orientation is-mandala based on the laid prevalent down in the wind direction and solar and lunar paths to ensure purification of the streets. Dimensions and form of the Shilpa shastras,Mandala are the determined main avenue on the basis laid of out natural from features east suchto west as hills, is cutforests across and water by twobodies major existing streets at the sitedelineated north to south and divide Jaipur into nine parts [26], [31]. This fairly regular layout of the streets and their orientation is based on the prevalent wind direction and solar and lunar paths to ensure purification of the streets. Dimensions and form of the Mandala are determined on the basis of natural features such as hills, forests and water bodies existing at the site [4]. The city of Jaipur had seven gates [6], the hilltop fort of Amber, which forms the nucleus of the present Jaipur, built between 1625 and 1666 [26].

Chandigarh:[4]. TheThe city first of Jaipurplanned had sevencity ofgates India [6], theafter hilltop 1947 fort was of Amber, Chandigarh which forms (Error! the nucleus Reference of the present source not found.), designedJaipur, built by between a French 1625 andarchitect 1666 [26] Le. Corbusier, and on the basis of a previously designed scheme by Albert Mayer, with a rectangular sectors on a grid-iron pattern for the fast moving traffic. A system of Chandigarh - The first planned city of India after 1947 was Chandigarh (Error! Reference source not found.), seven typesdesigned of roads by a wasFrench implemented architect Le Corbusier, in Chandigarh. and on the basis The of a streetspreviously divided designed the scheme entire by Albert area Mayer, of the city into sectors, thewith primary a rectangular module sectors of on the a grid city,-iron measuring pattern for the 800 fast metersmoving traffic x 1200. A system meters of seven for populationtypes of roads wasranging from 3000 to 20,000implemented based in onChandigarh. the plot-size The streets and divided topography the entire ofarea the of thearea. city Leinto Corbusier sectors, the primary personified module Chandigarhof the city, measuring 800 meters x 1200 meters for population ranging from 3000 to 20,000 based on the plot-size to compareand the topography urban functions of the area. with Le Corbusierthe capital personified complex Chandigarh forming to thecompare head, the theurban CBD functions as the with heart, the and the industrial andcapital educational complex forming areas the head,as the the twoCBD armsas the heart,[32]. and the industrial and educational areas as the two arms [32].

Figure 8 Plan of Jaipur [4] Figure 9 Le Corbusier’s plan for Chandigarh Fig. 8: Plan of Jaipur [4] (adaptedFig. 9: from Le Corbusier’s/2014-2015.nclurbandesign.org/) Plan for Chandigarh Reena Patra (2009) finds the plan of Chandigarh(adapted to resemble from the /2014-2015.nclurbandesign.org/) Vastu-Purusha-Mandala, the architectural mechanism for urban planning according[291 to] the Vastushastra, with the Capital Complex as the head located in north east, the Sukhna lake in the northeast, the city centre (Sector 17) is the brahmasthan, education and health institutions are in the north (the location of Mercury whose main attribute is health), cremation ground in the northwest or the darker part of the site, the industrial area placed to the southeast that is ruled by Agni and symbolises fire or concerned with the use of electricity, energy, power, whereas the residential areas are in the south and west, which are considered suitable for living purposes [5]. The designing of Chandigarh by Le Corbusier was considered to be a creative approach with regard to “light, air, ground, water and human beings”. Therefore important aspects of Vastushastra must be considered while planning and designing cities for promoting sustainable development of cities [5]. Amaravathi – Amravathi is the new capital of the state of Andhra Pradesh due to its reorganization and Hyderabad became the capital of Telangana. This city includes the ancient Amravathi, the capital of Satvahanas and Pallavas. The city is located on the Southern banks of Krishna river, designs to comprise 51% of green spaces and 10% of water bodies and is being planned on the principles of Vastushastra. The residential areas will be developed as clusters, and several such areas will constitute a township [33].

a. b. Figure 10a. Township Planning of Amaravathi (Andhra Pradesh Capital Region Development Authotity, 2019), b. Road Network 4. Discussion

The philosophy of Vastushastra aims to optimise benefits of the panchabhutas (five elements of nature), magnetic field of the earth, and rotation of the sun, moon and other planets through proper placement of e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Reena Patra (2009) finds the plan of Chandigarh to resemble the Vastu-Purusha-Mandala, the architectural mechanism for urban planning according to the Vastushastra, with the Capital Complex as the head located in north east, the Sukhna lake in the northeast, the city centre (Sector 17) is the brahmasthan, education and health institutions are in the north (the location of Mercury whose main attribute is health), cremation ground in the northwest or the darker part of the site, the industrial area placed to the southeast that is ruled by Agni and symbolises fire or concerned with the use of electricity, energy, power, whereas the residential areas are in the south and west, which are considered suitable for living purposes [5]. The designing of Chandigarh by Le Corbusier was considered to be a creative approach with regard to “light, air, ground, water and human beings”. Therefore important aspects of Vastushastra must be considered while planning and designing cities for promoting sustainable development of cities [5]. Amaravathi: Amravathi is the new capital of the state of Andhra Pradesh due to its reorganization and Hyderabad became the capital of Telangana. This city includes the ancient Amravathi, the capital of Satvahanas and Pallavas. The city is located on the Southern banks of Krishna river, designs to comprise 51% of green spaces and 10% of water bodies and is being planned on the principles of Vastushastra. The residential areas will be developed as clusters, and several such areas will constitute a township [33].

(a) (b)

Fig. 10(a): Township Planning of Amaravathi (Andhra Pradesh Capital Region Development Authotity, 2019), (b). Road Network

4. DISCUSSION The philosophy of Vastushastra aims to optimise benefits of the panchabhutas (five elements of nature), magnetic field of the earth, and rotation of the sun, moon and other planets through proper placement of different functions in the accurate direction and in appropriate zones. Its basic principles include the principle of orientation, site planning, principles of proportionate size of buildings, the six canons of Vedic architecture, and building aesthetics. Vastushastra provides environmentally aware town planning systems [5]. Vatushastra brings forth some of the simplest and most sustainable models of city planning, exhibiting several merits such climate responsive, compact and dense and activity or profession based allocation of residential quarters. The research paper discussed about the alignment of roads as well as building plans in these above mentioned cities elaborately. The traditional societies of the ancient cities were living according to their occupational hierarchical order. The climatic factor also play an important role in orientation of these cities. These cities are established in a systematic way without any congestion. Since sustainability of any place is determined based on wind, light in a proper pattern.

[292] Sustainable Urban Forms: A Critical Review of Vastushastra Cities developed from rectangular rural settlements divided into four parts by two main streets which crossed each other at right-angles in the centre. A capital city had three royal highways in the east-west direction and three north-south, dividing the city into 16 sectors, each sector having a specific type of land-use, depending upon the profession or caste of its inhabitants [10]. Well-built, well-protected and well-maintained roads and highways were “characterised by great width, necessitated by the various types of religious and ritual processions, and their grandeur prevented narrowing” due to encroachment. Traditional knowledge is important in controlling human aspirations and ensuring interdependence and sustainability. “Therefore, a serious consideration of sustainable philosophy is required by taking traditional concepts on the subject as a model.” Vastushastra represents a model for sustainable development. The critical regionalism of Vastushastra and its skilful use of by sthapati (Architect) provided environmentally aware town planning systems. It helps to maintain the hygienic condition of the city by orienting the road and alignment of the building in such way that wind and light can pass easily to every building and streets. According to Dutt, houses were built east to west for good ventilation since the prevailing wind in India blows from north or south throughout the year. However, to admit sunlight, the houses must also open out towards the east [6]. Hence the conclusion of this research paper tells that sustainability of the cities can be achieved based on the above discussion in order to maintain and preserve the aesthetic and natural beauty of these particular places from ancient to modern time line.

5. CONCLUSION Through this research, the authors have outlined the basic concepts of Vastushastra in detail including the various steps involved in planning of a town. The authors have further reviewed several towns, representing of the different urban phases in India that were planned according to the principles of Vastushastra. This has also provided evidence that this traditional system of urban planning has been continued over atleast five millennia. Finally the authors have analysed the sustainability of towns planned on the basis of Vastushastra. The major finding of this research based on the critical analysis of the some of the cities planned based on the vastushastra is that this traditional system that has been in existence since thousands of years is immensely suitable for planning to achieve sustainable urban forms even at present.

REFERENCES [1] C. B. Stringer and P. Andrews, “Genetic and fossil evidence for the origin of modern humans,” Science (80-. )., vol. 239, no. 4845, p. 4845, 1988. [2] S. M. Deshkar, “Kautilya Arthashastra and its relevance to Urban Planning Studies,” Inst. T. Planners, India, vol. 7–1, no. March, pp. 87–95, 2010. [3] R. Sharma, N. Aggarwal, and S. Kumar, “Ecological Sustainability in India through the Ages,” Int. Res. J. Environ. Sci., vol. 3, no. 1, pp. 70–73, 2014. [4] P. Das and P. Rampuria, “Thinking spatial networks today: The ‘Vastu Shastra’ way,” in Proceedings of the 10th International Space Syntax Symposium, 2015, pp. 1–15. [5] R. Patra, “Vaastu shastra: Towards sustainable development,” Sustain. Dev., vol. 17, no. 4, pp. 244–256, 2009. [6] B. B. Dutt, Town Planning in Ancient India. Delhi: Vishal Kaushik Printers, 1925. [7] R. Mookerji, Chandragupta Maurya and His Times. Delhi: Motilal Banarsidass, 1943. [8] A. S. A. Yang, Bazar India: Markets, Society, and the Colonial State in Bihar. Berkeley: University of California Press, 1998. [9] R. T. Patra, “Town Planning in Ancient India : In Moral Perspective THE INTERNATIONAL JOURNAL OF HUMANITIES & SOCIAL STUDIES Town Planning in Ancient India : In Moral Perspective,” no. September, 2016. [10] A. Sinha, “Design of Settlements in the Vaastu Shastras,” J. Cult. Geogr., vol. 17, no. 2, pp. 27–41, 1998. [11] A. Nagaich, “Climate Change and Ancient Indian Town Planning Ancient Indian Town Planning Principles and Bye-Laws,” Dharma Today, May-2017. [12] A. B. Reddy and A. Almoori, “Built on the principles of Vaastu sastra - Hyderabad - The Hindu,” The Hindu, Hyderabad, Aug-2012.

[293] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

[13] C. A. Petrie et al., “Adaptation to Variable Environments, Resilience to Climate Change: Investigating Land, Water and Settlement in Indus Northwest India,” Curr. Anthropol., vol. 58, no. 1, pp. 1–30, 2017. [14] J. R. McIntosh, The Ancient Indus Valley: New perspectives. Santa Barbara: www.abc-clio.com, 2008. [15] M. Danino, “New Insights into Harappan Town-Planning, Proportions and Units, with Special Reference to Dholavira,” Man Environ., vol. XXXIII, no. 1, pp. 66–79, 2008. [16] I. Douglas, Cities: An Environmental History. New York: I. B. Tauris & Co Ltd, 2013. [17] R. S. Bisht, “Dholavira Excavations: 1990-94,” Facet. Indian Civiliz., 1997. [18] H. Civilization, I. Civilization, I. Valley, H. Culture, H. Civilization, and S. Asia, “Harappan civilization 3.1,” 1950. [19] P. Sinha, “Sisupalgarh: The Lost City The population of Sisupalgarh was twice that of Athens,” https://www.livehistoryindia. com/amazing-india/2017/06/22/sisupalgarh-the-lost-city, 2019. [Online]. Available: https://www.livehistoryindia.com/ amazing-india/2017/06/22/sisupalgarh-the-lost-city. [20] R. K. Mohanty, M. L. Smith, T. Matney, A. Donkin, and G. A. Greene, “Archaeological Research at Sisupalgarh 2007: An Early Historical City in Orissa,” Puratattva, Bull. Indian Archaeol. Soc., vol. 37, 2007. [21] M. L. Smith, “The archaeology of South Asian cities,” J. Archaeol. Res., vol. 14, no. 2, pp. 97–142, 2006. [22] A. Ghosh, An Encyclopaedia of Indian Archaeology. New Delhi: Munshiram Manoharlal Publishers, 1989. [23] R. Ray, “Sisupalgarh: Fortified Urban Center of Early Historic India,” Teach. South Asia An Internet J. Pedagog., vol. III, pp. 3–10, 2007. [24] D. Schlingloff, Fortified Cities of Ancient India: A Comparative Study. 2014. [25] G. Michell, “City as Cosmogram: The Circular Plan of Warangal,” South Asian Stud., vol. 8, no. May 2015, pp. 1–17, 1992. [26] E. B. Havell, Indian architecture, its psychology, structure, and history from the first Muhannadan invasion to the present day. London: John Murray, 1913. [27] A. Petersen, Dictionary of Islamic Architecture. London: Routledge, 1996. [28] S. A. N. Rezavi, “Hydraulics and Water Management at Fatehpur Sikri,” in History of Science and Technology, R. L. Hangloo, Ed. New Delhi: Rawat Publications, 2011, pp. 131–146. [29] C. B. Asher, The New Cambridge History of India: Architecture of Mughal India. Cambridge: Cambridge University Press, 1992. [30] J. G. Harris, The First Firangis: Remarkable Stories of Heroes, Healers, Courtesans & Other Foreigners who Became Indian. New Delhi: Aleph Book Company, 2015. [31] P. Mitter, “The Early British Port Cities of India: Their Planning and Architecture Circa 1640-1757,” J. Soc. Archit. Hist., vol. 45, no. 2, pp. 95–114, 1986. [32] J. Crabtree, “Le Corbusier’s Chandigarh: an Indian city unlike any other,” Financial TImes, Jul-2015. [33] A. D. Corp, A. Pradesh, C. Region, and D. Authority, “Amaravati urban design strategy.”

[294] Rejuvenation and Redevelopment of Bellandur Lake Region of Bengaluru

Kanvi Tiwary1, Anjali Sharma2 and Ravish Kumar3 1Urban and Regional Planner, Architecture Department, National Institute of Technology Patna, Bihar, India 2,3Assistant Professor, Architecture Department, National Institute of Technology Patna, Bihar, India

ABSTRACT Once known as the city of lakes Bengaluru is now known as the city of burning lakes. Disposal of sewage, industrial effluents, garbage dumping and encroachment has degraded the water quality of the lakes to such an extent that they have become cesspools and their water far from being consumable, are nuisance to the city’s residents, spewing froth and foam and also burst into flames occasionally. Recent estimates of population reveal that Bengaluru already has qualified to the list of megacities, standing at the fourth position, after Delhi, Mumbai and Kolkata. Growth of the city’s population at an unprecedented scale is further compounding to the problems that already exist. The lakes that once acted as the source of water to the city have either vanished or reduced to small pools filled with filth and sewage. Most of the remaining lakes are so polluted that they spew froth and foam, when the wind velocity is high. However, it is Bellandur lake that is the most severely polluted, and the evidence comes from the fire that erupts from it every now and then. In contradiction to water scarcity, the city has witnessed unprecedented floods in the recent past due to encroachment and silting of the lakes, which once acted as sponges during heavy downpour. This paper analyses the issues related to Bellandur lake and suggests eco-friendly solutions to pollution of Bellandur lake along with urban design solutions towards its rejuvenation. The objectives of this paper are to 1) to analyse the issues related to the lake Bellandur; 2) examine the causes and sources of pollution in the lake and 3) propose remedial measures and solutions towards rejuvenation of the lake particularly with regard to (i) improvement of the water quality and suggesting measures to prevent further pollution, (ii) increasing its holding capacity, (iii) utilisation of the river water for urban needs to reduce the burden on river Cauvery and ground water and (iv) suggest some landscaping and urban design solutions towards rejuvenation of Bellandur lake As major findings, this paper has (1) identified innovative and eco-friendly techniques for water supply, replenishment of ground water, and rejuvenation of Bellandur lake; (2) made comprehensive recommendations for overall improvement of the water quality of the lake; (3) has proposed urban design solutions towards rejuvenation of the lake; and 4) suggested rigorous utilisation of ICT in operation, monitoring, management and control of the lakes Keywords: Bengaluru, Lakes, Bellandur, Water Scarcity, Cesspools, Sewage, Garbage, Encroachment, Eco-friendly Techniques, Karez

[295] Retrofitting for Daylighting of Existing Education Buildings: An Approach towards Sustainable Architecture

Alok Kumar Maurya1, Anjali Sharma2, Ravish Kumar3 and Ajay Kumar4 1Research Scholar, Architecture Department, National Institute of Technology Patna, Bihar, India 2,3,4Assistant Professor, Architecture Department, National Institute of Technology Patna, Bihar, India E-mail: *[email protected]

ABSTRACT Since over a decade there have been several researches related to sustainability and energy saving, with the aim to promote natural light in the educational buildings. However, research is lagging behind to a great extent on task-oriented daylighting of indoor spaces such as class rooms, laboratories, workshops etc. Even in India focus has once again shifted to energy conscious design especially with regard to proper use of daylight in educational buildings. The promotion of natural light in buildings enhances indoor working environment and cuts down the electricity usage. Properly implemented strategies of daylighting can reduce the environmental impact of buildings by approximately 60% of the electricity consumed in lighting of buildings. While it is easy to optimize the daylight while designing and constructing new building especially when these are based on trending design principles, it is not so in the case of existing buildings. Carl Elefante famously acknowledges that, “the greenest building is one that is already built.” Therefore the existing buildings must be retrofitted with modern daylighting techniques to reduce energy consumption, which in turn will reduce environmental impact. The objectives of this paper are to (1) investigate the associations of building elements, techniques and daylighting, explicitly the capacity of elements to decrease glare by reducing direct solar radiation and disseminating light more equitably while maintaining building character and visually comfortable indoor spaces; (2) explore design process of making educational building sustainable while meeting up the preferred objectives in daylight strategies. Keywords: Daylight, Sustainability, Visual Comfort, Educational Building

1. INTRODUCTION Daylighting contributes to sustainable development in two ways. First, an optimum daylighting level inside a space diminishes the requirement for artificial lighting and brings down the general energy consumption of the structure. Secondly, effective daylighting plans have demonstrated to improve inhabitant wellbeing and prosperity, additionally increasing inhabitant’s productivity. [1] Educational buildings are the places where students learn, gain knowledge and study. This place should be secure, safe, comfortable, and also must have an ambient environment. The productivity and learning skills are enhanced if the working conditions include adequate daylight and thermal comfort.[1] Every educational institution should utilize daylight as the essential source of light. Proper daylight provides best quality of visual perceptions while reducing the dependence on artificial means. Maintaining ambient environment in buildings consumes huge amount of energy and incurs an increase in operational cost. A rapidly urbanizing nation, such as India, with sustainable development as an important goal, the existing buildings which were designed and constructed earlier when energy was cheaper than today should undergo intense retrofit to meet the present energy challenges as well as the demands of the occupants. In India, energy generation is mostly done by fossil fuels, predominately coal. In year 2017–18 about three fourth of the total electricity generated was from coal. Approximately 8% of total electricity is consumed in commercial building in which 60% is used for lighting and 32% in HVAC. [2] [296] Retrofitting for Daylighting of Existing Education Buildings: An Approach towards Sustainable Architecture In these buildings various types of task, work or activities are performed on tables/working counters or on white/black boards, for which controlled admission of light is required within the room to prevent glare and other problems. Sometimes we use computer aided system like projectors, interactive whiteboard etc. where installation of controllable artificial light and shading devices to adapt indoor lighting condition becomes necessary. Glare is one of the prevailing problems in class rooms and lecture halls. It is created when a part of the field view is significantly brighter than the overall brightness of the remaining part of the visual scene. There are two types of glare, according to Kesten and Tereci (2016): Disability glare and Discomfort glare. Some glare can be tolerated if the workplace contains a view to the outside.[3] The objectives of this paper are to (1) investigate the associations of building elements, techniques and daylighting, explicitly the capacity of elements to decrease glare by reducing direct solar radiation and disseminating light more equitably while maintaining building character and visually comfortable indoor spaces; (2) explore design process of making educational buildings sustainable while meeting up the preferred objectives in daylight strategies.

2. MATERIALS AND METHODS This paper is based on qualitative research. For conducting this research large number of books, journals, newspaper articles, magazines, conference proceedings etc. have been referred, to apart from internet based sources, working papers as well as personal interview and reconnaissance survey which have also played a significant role in preparing this particular research paper in an elaborate way.

3. RESULTS First we investigate the building elements which are directly associated with daylight admission within the buildings. These building elements are crucial in managing daylight and creating ambient indoor environment. Some of the building elements are listed as follows:

3.1 Window or Glazing Windows are significant especially for conveying daylight and for providing view. Indoor spaces without windows are in general not liked and are occasionally unlawful. Windows are by and large observed alluring with sunlight, ventilation and see-out. They additionally provide data regarding progression of time as well as climate conditions. Windows significantly affect environmental variables, for example, thermal comfort, supply of fresh air, energy efficiency and noise interruption. So, windows are complex and vital for sustainable building design and must therefore be carefully considered. “The ratio of glazed area to the floor area is known as glazing ratio. This ratio ranges from 5% to 30% approximately. When windows are only on one side of a room then glazing should be 35% of the length of the wall”.[4]

3.2 External Shading Device These shading devices may be vertical, horizontal, inclined or Brise Soleil. They are used to decrease or totally cut the incoming sunlight in the summer season. Brise Soleil is a type of shading device which

[297] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) reduces solar heat gain within the building by deflecting sunlight. It allows the indirect component of sunlight inside the building through “multiple reflections” from the external blade/louvers to the interior ceiling while it blocks the direct sunlight. (Fig.1a)

(a) (b) Fig. 1: (a) Geometrical Parameters of the Brise Soleil (b) Design of External Overhangs by Means of Shading Angle [5]

3.3 Skylight/ Atrium Skylight or atrium is the part of or full roof system respectively of a building which is provided for admittance of daylight. Skylight can be covered with transparent sheets or it may be uncovered.

Fig. 2: Oculus (Skylight) in Pantheon, Rome [6] These are the major elements which have been identified and play a crucial role in retrofitting of buildings for improved daylight. Other than these elements there are some techniques which can be adopted for retrofitting. Some of the techniques (Re-directing systems) are listed below: a. Light shelves b. Light pipes c. Anidolic system

3.3.1 Light Shelves Frequently, classrooms lit only on one side not only need shading over windows to avoid excessive light but also need some re-directive lighting system which can distribute the light evenly throughout the room. Light shelves are best suited for the south oriented classroom. Best position of light shelves, is 2m above the floor and with an inclination of 10º from the horizontal.

[298] Retrofitting for Daylighting of Existing Education Buildings: An Approach towards Sustainable Architecture

Fig. 3: Light Shelves When Abundant Daylight Available [7]

3.3.2 Light Pipes These gadgets utilize a highly reflective film on the inside of a cylinder to channel light from a lens at the rooftop, to a lens at the ceiling. Light pipes are in general much smaller than an ordinary skylight, yet they convey adequate daylight to reduce the usage of electric lighting.

Fig. 4: Light Pipes [8]

3.3.3 Anidolic System Anidolic lighting utilizes non-imaging mirrors, lenses, and light guides to capture outside daylight and direct it profoundly into rooms, at the same time dissipating beams to dodge glare.

Fig. 5: Anidolic Lighting System [9]

[299] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 4. DISCUSSION Above mentioned building elements and daylighting techniques can easily enhance the daylight quality within buildings. These techniques can be opted for retrofitting on case specific basis. Building elements like window, shading device, skylight are the major sources from which controlled admission of the daylight is allowed but these building elements can create glare and other visual problems. Daylighting techniques (Re-directive system) can overcome these problems and provide visually and thermally pleasing indoor environment. Table 1 provides all the design considerations for the retrofitting in educational buildings.

Table 1: Design Solutions for Retrofitting [5]

Design Solution Feasible for Retrofitting Remarks Windows geometry and Partially Yes Many arrangements of different type of windows geometry were size; Glazing optical (As changing the geometry evaluated to capture more daylight with even distribution. The properties of windows requires more daylighting examination is combined with a thermal investigation work and money so it can be evaluating overheating dangers or potentially the vitality interest partially done to necessary for indoor heating and cooling and electrical lighting fixtures windows) energy consumption. Sometimes, the daylighting analysis is coupled with a thermal analysis assessing overheating risks and/ or the energy demand for space heating and cooling, as well as the artiﬁcial lighting system energy demand. Needs cautious thought of the influence of the encompassing condition. It redirects the direct sunlight upwards while allowing diffused Laser cut panels Yes light inside. These are available in translucent material or rolls which are Internal blinds Yes used to reduce glare if they are used with combination of external shading devices. Overhangs are mostly used for south orientated windows which Overhangs Yes do not permit summer radiations inside. These are used for east and west orientated windows. Fixed Louvers Yes louvers are often provided with internal blinds which are used under clear sky condition. Works best in downward inclined angles and 1:1 screens depth Solar screens Yes ratio which reduces the chances of glare. External translucent blinds with combination of light shelves Movable blinds Yes provides uniform illumination within the room When used in combination with clerestory it gives enhanced Light shelves Yes daylight factor with uniform distribution inside the room when sky conditions are clear. Light pipes Yes It can increase illuminance by 30% when sky condition is cloudy. Daylighting design/retrofitting is a promising new innovation that significantly affects the academic performance of students, can potentially enhance the environment for education and can lessen the use of energy. The position and measuring of the windows are the most crucial issues in the design for daylighting. Daylight primarily affects the internal illumination. Reducing the consumption of energy in buildings particularly in educational institutions is a significant outcome of daylighting design. Daylight design potentially saves cost significantly, despite an increase in the incremental initial cost by approximately INR 35 to INR 52.50 per square foot of the carpet area for dimmers, ballast, fixtures and controls. The savings range from INR 35 to INR 14 per square foot annually depending upon the outdoor condition and daylighting design. Artificial lighting accounts for approximately 35 to 50 percent of the total energy consumed in commercial buildings. The waste heat generated by the artificial light source added to

[300] Retrofitting for Daylighting of Existing Education Buildings: An Approach towards Sustainable Architecture the cooling loads and energy requirements for it, which can additionally be reduced upto 10 to 20 percent by using daylighting strategies. [10]

5. CONCLUSION Task oriented daylight increases in performance, comfort and productivity apart from reducing consumption of electricity to a large extent in internal illumination of buildings leading to sustainability. Through this paper, the authors have brought to light the association of different components of buildings with daylighting, particularly in terms of glare reduction and a more equitable distribution of daylight within indoor spaces and have identified building elements and daylighting techniques as strategies/solution as for daylight retrofitting of educational buildings, to not only make them visually comfortable and provide a thermally pleasing indoor environment but also by making them sustainable in the long run by reducing electricity consumption.

REFERENCES [1] C. Pierson, J. Wienold, and M. Bodart, “Review of factors influencing discomfort glare perception from daylight,” no. March, 2018. [2] N. Kaja, “An Overview of Energy Sector in India,” Int. J. Sci. Res., vol. 6, no. 3, pp. 2319–7064, 2015. [3] D. Kesten, A. Tereci, and K. Univeristy, “Daylight enhancement and lighting retrofits in educational buildings,” no. April, 2016. [4] T. Inan, “An investigation on daylighting performance in educational institutions,” Struct. Surv., vol. 31, no. 2, pp. 121–138, 2013. [5] V. Costanzo, G. Evola, and L. Marletta, “A Review of Daylighting Strategies in Schools: State of the Art and Expected Future Trends,” Buildings, vol. 7, no. 4, p. 41, 2017. [6] “No Title.” [Online]. Available: https://romeonsegway.com/10-facts-about-the-pantheon. [Accessed: 03-Jun-2019] [7] Y. Guan and Y. Yan, “Daylighting design in classroom based on yearly-graphic analysis,” Sustain., vol. 8, no. 7, pp. 1–17, 2016. [8] “No Title.” [Online]. Available: https://cleantechnica.com/2018/04/28/light-tubes-prism-lighting-other-daylighting solutions. [Accessed: 03-Jun-2019] [9] J. Scartezzini and G. Courret, “Anidolic daylighting systems,” no. November 2017, 2002. [10] G. D. Ander, “No Title,” U.S. Department of Energy Federal Energy Management Program (FEMP). [Online]. Available: https://www.wbdg.org/resources/daylighting. [Accessed: 03-Jun-2019].

[301] Analysis and Design of Stone Column using Different Techniques

Shubham Singh1 and L.B. Roy2 1M.Tech (4th Sem.), Geotechnical Engineering, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], E-mail: [email protected]

ABSTRACT The prediction of accurate ultimate bearing capacity of stone columns is very important in ground improvement techniques. The stone column is very useful in reducing the settlement of foundation soil and increasing the ultimate bearing capacity. This paper first offers parametric studies on the effects of contributing parameters such as stone column diameter, column spacing, area replacement ratio and internal fraction angle of the column material on the ultimate bearing capacity being investigated by using IS 15284 (Part 1): 2003. Second a comparison between predictions by IS Code method with other design method and test data is presented to verify the reliability of adopted method. Keyword: Stone Column, Ground Improvement, Bearing Capacity, Soft Clay

1. INTRODUCTION Construction over soft clay is always a great challenge to the geotechnical engineers. High compressibility and low shear strength make the soil unsuitable for construction. When such soil is encountered at site, then installation of stone columns is the best and simple alternatives to increase the supporting load capacity by improving the ground. The primary purpose of soil improved by stone column technique is mainly to increase the bearing capacity (Bouassida et al., 1995) of foundation soil and also to reduce the post-construction settlement. Also, due to high permeability of stone column material, consolidation rate in soft clay increases. Stone column method has been mainly used for low rise buildings and structures such as oil storage tanks, embankments, abutments, power plant foundations, etc. The effectiveness of the load transmitted by the stone-columns essentially depends on the lateral stress that exerts from the surrounding soft soil (Afshar and Ghazavi 2012). Normally, stone columns should not be used in soils with shear strength less than 14kN/m2 (Bell, 1993). Alamgir and Zaher (2001) illustrated that the standard penetration resistance of the soft ground has been increased significantly after a stone column installation. N-value increases from 2 to 7 for natural ground to 5 to 12 for the reinforced soft ground. Stone columns are constructed usually in triangular pattern and in square pattern. The equilateral triangle pattern gives more dense packing in a given area. In this paper, IS 15284 (Part 1, 2003) is used to study the different factors affecting the bearing capacity and finally to predict the bearing capacity of the stone columns. For this purpose, the basic parameters which governs the designing of stone columns such as diameter of column, centre to centre spacing between the columns, angle of internal friction of stone column material as well as of the surrounding soil, unit weight of the soil and area replacement ratio. After estimating the data, a critical analysis is done in the form of tables and graphs which shows change in the bearing capacity of the treated soil with change in the governing parameters. This paper also presents a comparison between predictions by IS Code method with other design method (Bouassida et al., 1995,) and test data (Maurya et al., 2006, Murugesan and Rajagopal, 2008) to verify the reliability of adopted method.

[302] Analysis and Design of Stone Column using Different Techniques 2. METHODOLOGY In the current work, IS 15284 (Part-I, 2003), method is used for the designing of the stone column. The load carrying capacity of the treated ground may be obtained by summing up the contribution of load capacity resulting from the resistance offered by the surrounding soil against lateral deformation, due to surcharge over it, and the bearing support provided by soil in between the stone columns.

2.1 Capacity Based on Bulging of Column σσ= K (1) v rl pcol

σσ=( + 4)CK v ro u pcol

Where,

σ rl = limiting radial stress = σ ro+ 4C u

σ ro = initial effective radial stress = Koσ vo

Ko = average coefficient of lateral earth pressure for clays equal to 0.6 σ σ vo = average initial effective vertical stress, i.e vo = γ 2D

2 ° ϕc K p = tan (45+ ) col 2

π 2 Safe load on column alone QD1 =(σ v × )/2 (2) 4

2.2 Surcharge Effect q ∆=σ safe (1 + 2K ) (3) ro 3 o

So, Increase in safe load of column, Q2 is given by the following formula: KA∆σ Q = pcol ro s (4) 2 2

2.3 Bearing Support Provided by the Intervening Soil Area of intervening soil for each column, π D2 AS=0.866 2 − (5) g 4

qAsafe g Safe load taken by the intervening soil, Q3 =

[303] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Table 1: Parameters and Ranges Parameter Ranges References Diameter, D 0.5m –1.5m Bell, 1993 Spacing, S 2D – 3D Mitchell And Katti, 1981

o o Friction angle, c 35 – 45 Nayak, 1982 φ 3. RESULTS AND DISCUSSION

3.1 Variation of Bearing Capacity with Diameter Table 2 shows the effect on the bearing capacity with various diameters of the stone column at different S/D ratios. It can clearly seen from the tables that, as the S/D ratio increases, the bearing capacity of the stone column decreases.

3 Table 2: Variation of Bearing Capacity with Diameter at Different S/D Ratios and at φc = 35, γ =16KN/m B.C (q) D S/D=1 S/D=1.5 S/D=2 S/D=3 S/D=4 S/D=5 0.5 210.1 118.7 86.7 63.9 55.9 52.2 0.6 213.3 120.1 87.5 64.2 56.1 52.3 0.7 216.5 121.5 88.3 64.6 56.3 52.4 0.8 219.7 123.0 89.1 64.9 56.5 52.6 0.9 222.9 124.4 89.9 65.3 56.7 52.7 1.0 226.1 125.8 90.7 65.7 56.9 52.8 1.1 229.3 127.3 91.5 66.0 57.1 52.9 1.2 232.5 128.7 92.3 66.4 57.3 53.1 1.3 235.7 130.1 93.1 66.7 57.5 53.2 1.4 239.0 131.5 93.9 67.1 57.7 53.3 1.5 242.2 133.0 94.7 67.4 57.9 53.5

240 220 200 180 S/D=1 160 140 S/D=2 120 S/D=3 100 80 S/D=4 60 S/D=5 40 Bearing capacity (q) capacity Bearing 20 S/D=1.5 0 0.5 0.7 0.9 1.1 1.3 1.5 1.7 Diameter (D)

Fig. 1: Variation of Bearing Capacity with Diameter

[304] Analysis and Design of Stone Column using Different Techniques

3.2 Variation of Bearing Capacity with Friction Angle of Stone Material In the following tables, the change in bearing capacity with different values of angle of internal friction ( ) are presented with two set of diameter values i.e D =0.5 & D =1.5 at centre to centre spacing, c γ S = 2D, S=3D, S=1.5D for both the diameters. The cohesion (Cu) and unit density ( ) values are taken asφ 20kN/m2 & 19kN/m3 respectively.

Table 3&4: Variation of Bearing Capacity with Friction Angle of Stone Material D=0.5 & D=1.5 Respectively B.C (q) B.C (q) φ φ c S/D=1.5 S/D= 2 S/D=3 c S/D=1.5 S/D= 2 S/D=3 35 120.0 87.5 64.2 35 137.0 97.0 68.4 36 124.1 89.8 65.2 36 141.8 99.7 69.6 37 128.4 92.2 66.3 37 146.9 102.6 70.9 38 132.9 94.7 67.4 38 152.2 105.6 72.3 39 137.8 97.4 68.6 39 158.0 108.8 73.7 40 142.9 100.3 69.9 40 164.0 112.2 75.2 41 148.3 103.4 71.3 41 170.4 115.8 76.8 42 154.1 106.6 72.7 42 177.3 119.7 78.5 43 160.2 110.1 74.3 43 184.5 123.7 80.3 44 166.8 113.8 75.9 44 192.3 128.1 82.3 45 173.8 117.7 77.6 45 200.6 132.8 84.3

220

200 180 160 140 120 100 S/D=3 80 60 S/D=2 Bearing capacity (q) 40 S/D=1.5 20 0 35 37 39 41 43 45 Angle of internal Friction (φc)

Fig. 2: Variation of Bearing Capacity with Angle of Internal Friction φc (D=0.5m)

Fig. 3: Variation of Bearing Capacity with Angle of Internal Friction φc (D=1.5m)

[305] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) From the above graph, it can be observed that, as the value of angle of internal friction increases, the bearing capacity of the stone column increases. When the values of friction angle increases from 35 to 45, percentage change in bearing capacity is 34.57% for S= 2D and approx. 21% for S= 3D. Comparison of IS Code Method with Bouassida Method The results of IS Code method with those of Bouassida method is compared here. The unit weight of the native soil is γ =19 KN/m3 and stone column diameter is D =0.5 m. The center-to-center distance for stone columns is S =1.5 D, S = 2D, S =3D, S = 4D taken for analysis. Six types of native soil is assumed having c =35 to c = 45. φ φ

Fig. 4: Comparison of IS Code Method with Bouassida Method Figure 4 shows results of analysis for different internal friction angles for stone-column materials. As seen, the IS Code method gives relatively smaller data to those of Bouassida method, especially for S =2D, S =3D, S =4D. Comparison with Experimental Results Case 1 Maurya et al. conducted a large-scale test on a stone column in India. The stone columns were installed in a triangular pattern with S =4m, D =0.9 m. For stone column material, the density was γ c =22 kN/ 3 m and the friction angle was c =46. The ultimate load was about 800 kN for the single column test at a corresponding settlement of about 23mm. If the average cohesion of the soft soil is assumed 12 kPa, φ the IS Code method gives the stone column ultimate bearing capacity of qult = 56 kPa .The ultimate load becomes about 770 kN. This differs only - 4% from the measured capacity. Case 2 To 4 Murugesan and Rajagopal tested three single stone-columns having diameters of 5, 7.5, and 10 cm.. The load was applied on a plate having a diameter equal to twice the column diameter. The experimental results show that the ultimate load tolerated by single stone columns and native soil are 110 N, 320 N, and 620 N for stone-columns having diameters 5, 7.5, and 10 cm, respectively. The bearing support offered by clay in contact with the loading plate was qult =12.65 kPa , using Terzaghi method. The IS Code method gives qult =24 kPa for stone-columns with different diameter. The ultimate load becomes about 100 N, 200 N and 400 N for stone-columns with diameters of 5, 7.5, and 10 cm, respectively. These differs only - 9%, -37% and -33% from the measured forces for 3 columns, respectively.

[306] Analysis and Design of Stone Column using Different Techniques

Table 5: Difference between Measured and Predicted Values for Ultimate Loads Carried by Stone Columns Case No. Case1 Case 2 Case 3 Case 4 Measured ultimate load (N) 800 110 320 620 Predicted ultimate load using IS Code method(N) 770 100 200 400 Deviation between predicted and measured loads -4% -9% -37% -33% As shown for above five cases, the IS Code method under-estimates for all four cases (Table 5). Therefore, obviously the IS Code method has capabilities to determine the ultimate load carried by a stone column and thus is used subsequently to perform further analyses on stone columns.

4. CONCLUSIONS

The bearing capacity of stone column mainly depends on the friction angle ( c) of the stone column materials, diameter (d), spacing between the stone columns (S) and undrained cohesion (Cu) of the surrounding soft soil. So all these parameters were considered as inputs and bearingφ capacity of stone column was taken as output. The output results were verified using predictions by IS Code method with other design method (Bouassida et al., 1995,) and test data (Maurya et al., 2006, Murugesan and Rajagopal, 2008) to verify the reliability of adopted method. The adopted method showed reasonable agreement with the test carried out by other researchers. The following conclusions can be drawn based on the study: 1. The stone column bearing capacity increases with increasing the friction angle of the stone material and the stone column diameter. 2. The stone column capacity decreases by increasing the stone column center to center distance to S/D=3 and beyond this value, the decrease of the stone capacity is negligible. 3. If the spacing is less than twice the diameter, then overestimated values of bearing capacity is obtained which is not safe. 4. The IS Code method gives safer values of bearing capacity when compare with other design methodologies. As shown from the experimental cases, the IS Code method over-estimates the ultimate load for one case and under-estimates for four cases. 5. The use of stone columns is more efficient in softer cohesive soils.

REFERENCES [1] Ambily, A.P. and Gandhi, S.R. (2007). “Behavior of stone columns based on experimental and FEM analysis.” J. Geotech. Geoenviron. Eng., 133(4), 405–415. [2] Bouassida M, De Buhan P, Dormieux L. Bearing capacity of a foundation resting on a soil reinforced by a group of columns, Ghotechnique, 1995, No. 1, Vol. 45, pp. 25-34. [3] Huges J.M.O. and Withers N.J.( 1974) Reinforcing of soft cohesive soils with stone columns, Ground Eng, 1974, No. 3, Vol. 7, pp. 42-49. [4] IS 15284 (Part 1): 2003, Design and Construction for ground improvement — Guidelines. PART 1 Stone Columns. [5] Maurya R.R, Sharma B.V.R, Naresh D.N. Footing load tests on single and group of stone columns, 16th International Conference on Soil Mechanics and Geotechnical Engineering, Osaka, Japan, 2005, pp. 1385-1388. [6] Mitchell, J.K. and Katti, R.K. (1981) Soil Improvement: State of Art Report.Proceedings 10th International Conference on SMFE, Stockholm, p.163. [7] Murugesan S, Rajagopal K. Studies on the behavior of single and group of geosynthetic encased stone columns, Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 2010, No. 1, Vol. 136, pp. 129-139. [8] Nayak, N.V. (1982)Stone column and monitoring instruments, Proceedings Symposium on soil and rock improvement: geotextiles, reinforced earth and modern piling techniques, Asian Institute of Technology, Bangkok. [9] Mitchell, J.K. and Katti, R.K. (1981) Soil Improvement: State of Art Report.Proceedings 10th International Conference on SMFE, Stockholm, p. 163.

[307] Study of Land Use Change on Soil Erosion in Sone Command Area using Remote Sensing and GIS Techniques

K. Praveen1, Animesh Pandey2 and L.B. Roy3 1Ph.D, Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2M.Tech. 2nd Year, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 3Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Land distortion is a big environmental and economic challenge in all over the globe. Soil erosion is caused by various reasons, but the water slope and poor land management are the some main causes. Identification of erosion prone areas is the most important in the present time for agricultural planning and effective land management. This study includes estimation of annual average soil loss in the Sone command area in Bihar and preparation of spatially distributed soil erosion map at different land use scenario. A well-known empirical equation RUSLE (Revised Universal Soil Loss Equation) is used for estimation of parameters and preparation of spatially distributed maps. By using Remote sensing and GIS Techniques different soil loss parameters like rainfall erosivity(R), soil erodability( K), slope length and steepness factor(LS), cover management factor (c) and conservation practice factor(p) are estimated and spatially distributed map of all these parameters are prepared. Average soil loss in the study area is found in the ranges 21 to 40 t.ha.yr-1 and maximum value is found to be around 7000 t.ha.yr-1 areas having high soil erosion rate is very less. Keeping other factor constant cover management factor for different land cover pattern is calculated and spatially distributed soil loss map is prepared at different conditions. Because study area is lies in plain range hence points having high soil erosion rate is very less. Keywords: Land Distortion, RUSLE (Revised Universal Soil Loss Equation), Rainfall Erosivity (R), Soil Erodability (K), Steepness Factor (L) and Cover Management Factor (c)

1. INTRODUCTION Soil separation is a method in which it includes separation, transport and collection. By the momentum of water, soil is separated from the soil surface. By the effect of water top vegetation is weakened and soil has probability to transport downward in the direction of flow. Due to soil erosion poetically irrigated field converted into an unused field due to climatic change soil disintegration reduces collecting limit of the downstream and reduces the capacity of watershed. Sediment yield at the downstream side is closely related to surface stream characteristics. So any mismanagement in measurement in surface runoff is given wrong estimation of sediment yield. Around the globe about fifty present of the pastureland and eighty present agriculture fields experience the deficient effect of soil erosion. Around globe six million ha profitable area being lost due soil disintegration related problems. In India also land disintegration becomes a significant problem. Figuring of the sediment yield from different watershed zones has spatially, momently and social connection to calculate sediment yield various models are used. Some straightforward methodologies like Universal Soil Loss Equation (USLE; Wischmeier and Smith 1978), Modified Universal Soil Loss Equation (MUSLE; Williams 1975) or Revised Universal Soil Loss Equation (RUSLE; Renard et al., 1991), are frequently utilized for estimation of gross measure of surface disintegration in watershed zones. Land degradation is one of the most serious global environmental problems of modern Time, threatening agricultural areas at an alarming rate. Land degradation happens when natural or anthropogenic processes reduce the quality of land by decreasing the ability of land to support crops, livestock and organisms. Water [308] Study of Land Use Change on Soil Erosion in Sone Command Area using Remote Sensing and GIS Techniques is the most common cause for soil erosion, which is accelerated by poor land use and land management practices. Land use pattern in areas prone to soil erosion indicates that areas with natural forest cover in the head water regions have minimum rate of soil erosion while areas with human intervention have high rate of soil erosion (V. Prasanna Kumar et al.,). Lands are moderate erosion risk category it is highly occurred in the fallow land. The severe erosion mainly occurred in forest and barren rocky land (P. Karthick et al.,).A good plant cover is generally capable of preventing surface erosion indicated that the loss of soil erosion can be greatly reduced by a higher vegetation cover For the large scale soil conservation, little work can be done to reduce rainfall and runoff erosivity, soil erodibility, slope length and slope steepness, so vegetation restoration and support practice would be the way to reduce the soil loss risk.( P.Zhou et al.,). study estimate soil erosion and sediment yield using existing conceptual methods and GIS can be useful for the identification of sediment source areas and prediction of sediment yield at a catchment scale with available optimum data sets (Rabin Bhattarai et al.,).

2. STUDY AREA The area chosen for the study is the southern part of Bihar in India. Total length of Sone River is 881 km. Sone River originates near Amarkantak in Madhya Pradesh. Sone River is an important tributary of Ganga River. The study area also include indrapuri barrage situated at dehri on Sone. The total length of Sone River is 784 km. Total catchment area of river is 70,055 sq km. Sone command covers 8 district namely Patna Aurangabad, Jahanabad, Gaya, Bhojpur, Baxur, Rohtas, Bhabhua of Bihar. Mean annual rainfall in the study area is 1398 mm. The project is situated at latitude 24º18´N to 24º59´ and longitude 84º 06´to 85º1´ E. the total Sone command area is 130.25 ha. Soil type of the study area is usually clay loam. Major land use pattern of study area is vegetation, water, barren land, urban, rock.

Fig. 2.1: Sone Command Area

3. METHODOLOGY A well-known empirical equation known as Revised Universal Soil Loss equation is used for determination of soil loss and spatially distributed soil loss map is prepared for determination of points of maximum soil erosion. The exaction of RUSLE is expressed as. A= R.K.LS.C.P A= Computed spatial average soil loss over a period, R = rainfall-runoff erosivity factor (MJ mm ha-1hr-1), K= soil erodibility factor, LS=slope length steepness factor, C is the cover management factor and p is support practice factor. [309] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Data required for RUSLE factor generation Average annual rainfall data for R factor, Land sat eight images for cover management factor DEM (30mx30m) for slope length factor generation FAO soil data for K-factor generation. Rainfall Erosivity (R) For our study we use the empirical formula generated by (sing et al. 1981) R = 79 + 0.363*RN Where: RN is the average annual rainfall in mm Sone command area lies in 8 district of Bihar so rain fall data of 8 district of Bihar are used for preparation of spatially distributed R- factor map. Sites from outside the watershed boundary also were selected as it would give us a more accurate interpolated result Soil Erodibility Factor (K) The soil type’s map was obtained from the digital soil map of the world by food and agriculture organization of the United Nations, Version 3.6 and completed January 2005 soil erodiblity factor is calculated using following table.

Mean k(based on % Organic Content) Textural Class Unknown < 2% >2% Clay 0.22 0.24 0.21 Sandy clay 0.2 0.2 0.2 Silty clay 0.26 0.27 0.26 Sand 0.02 0.03 0.01 Sandy loam 0.15 0.14 0.12 Clay loam 0.3 0.33 0.28 Loamy sand 0.004 0.005 0.04 Silty clay loam 0.32 0.35 0.3 Silty loam 0.3 0.34 0.26 Silt 0.38 0.41 0.37 Sandy clay loam 0.2 0.2 0.2 Slope Length and Steepness Factor (LS) The impact of geography on soil disintegration is represented by the LS factor in USLE, which consolidates the impacts of a slant length factor, L, and an incline steepness factors. The LS factor is calculated using modification of the empirical equation of Wischmeier and Smith, 1978 by Moore and Wilson (1992) using Spatial Analyst tool of ArcGIS from equation: [LS= power (“flowaccu”* cell size/22.1, 0.4) *power (sin (“slope_deg”*0.01745)/0.09, 1.4) *1.4) Cover Management Factor (C) The cover management factor (C) represents the effects of fruitarian, management, and erosion control practices on soil loss. As with other USLE factors, the C value is a ratio comparing the existing surface conditions at a site to the standard conditions. Van der knijff (1999) equation is used for determination of cover management factor C= exp

Where

For NDVI α=2, calculation β=1 purpose we use band 4 and 5 of Landsat8 image because band4 and band5 represents near infrared and red band of the spectrum. [310] Study of Land Use Change on Soil Erosion in Sone Command Area using Remote Sensing and GIS Techniques Land sat image of year 2014, 2016, 2017 and 2019 are used to calculate of NDVI values. Corresponding values of NDVI values of C- factor is calculated. Support Practice Factor (P) By definition, the help practice factor (P) in RUSLE is the proportion of soil misfortune with a particular help practice to the relating misfortune with upslope and downslope culturing. For this study support practice factor is assumed as 1.

4. RESULT AND DISCUSSION Computed pixel wise different parameters values Following are 5 parameters used for calculating sediment yield 1. Rainfall runoff erosivity factor (R): 449.623 ~ 494.m42 MJ mm ha-1 hr-1 2. Soil erodibility factor (K): 0.05~0.34 3. Slope length factor & slope steepness factor (LS): 0 ~ 64.7205 4. Cover management factor (C): 0.1029 ~ 1 .449) Support practice factor (P): 0.28~1

Fig. 4.1: Spatially Distributed R-Factor Map Fig. 4.2: Spatially Distributed K-Factor

Fig. 4.3: Slope Length and Steepness Factor Map Fig. 4.4: Cover Management Factor Map 2016

[311] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 4.3: Slope Length and Steepness Factor Map Fig. 4.4: Cover Management Factor Map 2016

Fig. 4.5: Cover Management Factor Map 2014 Fig. 4.6: Cover Management Factor Map 2017

Fig. 4.7: Soil Erosion Map 2019

[312] Study of Land Use Change on Soil Erosion in Sone Command Area using Remote Sensing and GIS Techniques

Fig. 4.8: Spatially Distributed Soil Loss Map Fig. 4.9: Soil Erosion Map

Fig. 4.10: Spatially Distributed Soil Erosion Fig. 4.11: Soil Erosion Map

REFERENCES [1] Arabinda Sharma, Kamlesh.Tiwari, P. B. S. Bhadoria,(2010) Effect of land use land cover change on soil erosion potential in an agricultural watershed. Environ Monit Assess 173: 789–801. [2] Karine Vezina,Ferdinand Bonn,Cu Pham Van(2006) Agricultural land-use patterns and soil erosion vulnerability of watershed units in Vietnam’s northern highlands . Landscape Ecol (2006) 21:1311–1325. [3] P. Karthick,C. Lakshumanan and P. Ramki(2017) Estimation of soil erosion vulnerability in Perambalur Taluk, Tamilnadu using revised universal soil loss equation model (RUSLE) and geo information technology International Research Journal of Earth Science 2321-2527 [4] Zhanyu Zhang, Liting Sheng, Jie Yang, Xiao-An Chen, Lili Kong and Bakhtawar Wagon (2015) Effects of Land Use and Slope Gradient on Soil Erosion in a Red Soil Hilly Watershed of Southern China. [5] Sumantra Sarathi Biswas,Padmini Pani (2015) Estimation of soil erosion using RUSLE and GIS techniques: a case study of Barakar River basin, Jharkhand, India. [6] P. Zhou, J. Nieminen, T. Tokola ,O. Luukkanen.Oliver (2006) Large scale soil erosion modeling for a mountainous watershed WIT Transaction on ecology and environment vol. 89. [7] Anita K.Prakash,I.V.Muralikrishna, P.K.Mishra and R.V.R.K.Chalam (2007) Deciding Alternative Land Use Options in a Watershed Using GIS J. Irrig. Drain Eng., 2007, 133(2): 162-174. [8] Revised Universal Soil Loss Equation HANDBOOK [9] District survey report by Central Ground Water Board District Survey Report Patna, Aurangabad, Bhojpur, Buxar, Rohtas, Gaya, Jahanabad, Balia.

[313] Pond Ash Mixing Effect on the Properties of Soil to be Used for Subgrade Construction

Diksha Singh1, U.K. Maheshwari2 and N.K. Saxena3 1P.G. Scholar, Department of Civil Engineering, K.N.I.T. Sultanpur, (U.P.), India 2Professor & Head, Department of Civil Engineering, K.N.I.T. Sultanpur, (U.P.), India 3Professor, Department of Civil Engineering, K.N.I.T. Sultanpur, (U.P.), India E-mail: [email protected], [email protected], [email protected]

ABSTRACT The waste generation in the world is increasing due to increase in population, construction activities, socio-economic activities etc. and it generally represents the agricultural, industrial and commercial or construction waste. The environmental concerns force us to either minimize waste production or reuse/ re-cycle this. Among various methods available, the simplest method is to utilise this waste as additives for soil stabilisation of required soil. Based on the literature review and considering the above point, the present paper focuses to assess the impact of adding pond ash (PA) in the locally available CL soil to be used for subgrade construction of rural roads. To accomplish this, the experimental data have been collected for the CL soil mixed with four different percentages of pond ash (i.e. 0%, 10%, 20% and 30% by weight). The analysed result for strength in terms of CBR and permeability shows that CBR values obtained have an increasing trend at all mix proportions with maximum increase of approximately 125% at 30% mix percentage. The same trend is also observed for permeability values for all the mix proportions. Keywords: Stabilisation, Pond Ash, CBR, Permeability, Waste

1. INTRODUCTION Soil is the valuable natural resource consists of many layers of mineral constituents, which is formed due to disintegration of parent minerals by weathering (physical or chemical). The soil exhibits the characteristics from cohesionless to highly cohesive. Generally, the engineering properties for cohesive soil are more complex due to its high compressibility, low permeability and poor strength. Therefore, it is necessary to improve the engineering properties of such types of soil. As we know that the present world is facing a complex problem of increased production of waste generation due to industrial activities. The growth of such wastes necessitates to prominently using these wastes for construction or other activities. In India maximum power is generated using thermal power plants by burning the coal. Pond ash is the waste product from boilers of thermal power plants and the rapid growth in volume of pond ash requires increased utilization by safe disposal methods. Kumar and Gupta (2016) concluded that clay mixed with optimum % of RHA and PA can be used as fill material for geotechnical applications. Ghosh et al. (2010) studied the suitability of stabilized PA for road subgrade construction in combination with lime and phosphogypsum. Bera A.K. (2010) reported that value of CBR changes considerably with increase in % of pond ash mixed with soil. Roy and Chattopadhyay (2008) shown that with the addition of RHA and PA compaction characteristics of alluvial soil are influenced significantly. Kumar et al. (1999) investigates the effect of sand and pond ash reinforced with randomly distributed polyester fibres. They showed the results in the improvement of various characteristics of soil. As per the literature review available, wastes such as pond ash are used to improve the engineering properties of existing soil. The specific objectives of the present study are:

[314] Pond Ash Mixing Effect on the Properties of Soil to be Used for Subgrade Construction a. To evaluate the engineering properties of selected local soil and its classification. b. To determine the changes in various properties like (specific gravity, atterberg’s limits, OMC, MDD) of selected clayey soil (CL in present case) when added with different proportions of pond ash. c. To determine the changes in CBR or permeability values of selected clayey soil (CL in present case) when added with different proportions of pond ash. d. The present study may be useful in field by lowering the construction costs as well as increasing the life of pavement with increased strength of soil using waste materials in environment friendly way.

2. MATERIAL USED

2.1 Soil The soil samples were taken for the study was obtained near the site from the Sultanpur-Faizabad road in Sultanpur district of Uttar Pradesh, India. The soil thus obtained was carried to the laboratory in sacks. After that the soil was air dried for two to three days and the grains of soil are crushed in small size and sieved carefully before the study. The details of the sample preparation and testing procedures were followed as recommended by IS 2720. The properties of the soil sample can be summarized as follows in Table 1:

Table 1: Physical Properties of Soil Properties Observed Values Specific Graviy 2.672 Gravel- Sand (%) 0.6 Silt (%) 62.9 Clay (%) 36.5 LL 33 PL 24.63 PI 8.37 Soil classification as per IS:1498-1970 CL (Silty clay of Low compressibility) OMC (%) 18.6 MDD (kN/m3) 17.20 Soaked CBR 5.21 Coeff. Of Permeability (K) (cm/s) 9.053 × 10-6

2.2 Pond Ash Pond ash is the by-product of thermal power plants, which is considered as a waste material. It is a grey coloured particle which is coarser in size than other ashes released from thermal power plants. Besides this steel, copper and aluminium plants also contribute a substantial amount of pond ash. Its disposal is a major problem from environmental point of view. Pond ash is a resource material which should be utilized. The pond ash used in this study was collected from the Thermal power plant located in Tanda in Ambedkarnagar district of Uttar Pradesh, India. The samples were air dried and after that its physical properties are studied in Laboratory. The chemical composition of pond ash, which is given by NTPC Tanda is given in Table 2: [315] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Table 2: Chemical Composition of Pond Ash

S. No Properties Observed Values

1. Silica content (SiO2) 62.59 %

2. Iron Oxide (Fe2O3) 3.76 %

3. Alumina (Al2O3) 27.11 % 4. Calcium Oxide (CaO) 1.31 % 5. Magnesium Oxide (MgO) 0.88 % 6. Fineness (Blaine) (m2/kg) 264 7. Lime Reactivity (N/mm2) 5.2 8. Loss on Ignition 2.21 % The physical properties of the pond ash which is calculated in laboratory are as follows:

Table 3: Physical Properties of Pond Ash

Properties Observed Values Colour Grey Specific gravity 2.075 Gravel - Sand (%) 72.69 Silt - Clay (%) 27.31 OMC (%) 32 MDD (kN/m3) 9.78 Soaked CBR 8.37 Coeff. of Permeability (K) (cm/s) 1.133 × 10-4

2.3 Mix Proportions Samples of soil were prepared by mixing pond ash in the laboratory. Pond ash is mixed by weight with soil in varying percentages to obtain a homogeneous mixture. A laboratory testing program is planned to evaluate the properties of un-stabilized and stabilized soil samples. During the study, four samples were prepared by mixing pond ash and tests were carried out on these samples.

Table 4: Preparation of Test Samples

S. No. Sample Soil (%) Pondash (%) 1. 0 % PA 100 0 2. 10 % PA 90 10 3. 20 % PA 80 20 4. 30 % PA 70 30

3. EXPERIMENTAL RESULTS In this section, an attempt has been made to analyse the collected experimental data for the samples in an overall perspective for CBR and permeability and effect of addition of pond ash at varying percentages (0%, 10%, 20%, 30%) to the properties of the locally available soil used.

[316] Pond Ash Mixing Effect on the Properties of Soil to be Used for Subgrade Construction

3.1 Specific Gravity The specific gravity value obtained for CL soil is 2.672 while it is 2.075 for pond ash. In Figure 1 the variation of specific gravity shows, which reduces from 2.672 for original soil to minimum value of 2.255 due to replacement by 30% of pond ash.

Fig. 1: Variation of Specific Gravity with Addition of PA Therefore, it may be concluded that replacement by pond ash causes reduction in specific gravity of soil selected.

3.2 Plasticity Index The variation of plasticity index with the addition of pond ash is shown in figure 2. The value of plasticity index for original soil is 8.37 which are decreasing to the value of 7.21 by the addition of 30% pond ash into the soil.

Fig. 2: Variation of Plasticity Index with Addition of PA The pond ash used in the present study is non-plastic (NP) which justifies the above trend of reduction in plasticity index compare to the selected soil.

[317] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 3.3 OMC From figure 3, it can be easily seen that optimum moisture content of soil is 18.6 % which is further increases with increase in % of pond ash added till 20% and after that it shows a decreasing trend to the experimental data range tested.

Fig. 3: Variation of OMC with Addition of PA

3.4 MDD From figure 4, it can be easily seen that maximum dry density of soil is 17.2 kN/m3 which is further decreases with increase in % of pond ash added till 20% and after that it shows an increasing trend to the experimental data range tested.

Fig. 4: Variation of MDD with Addition of PA

3.5 CBR From figure 5, it is clearly seen that CBR value increases linearly with increase in % addition of pond ash in the soil and the soaked CBR value is maximum i.e. 11.72 at 30% pond ash proportion compare to the CBR value of original soil as 5.21.

[318] Pond Ash Mixing Effect on the Properties of Soil to be Used for Subgrade Construction

Fig. 5: Variation of CBR with Addition of PA It shows almost 125% increase in CBR value by the addition of pond ash which represents an appreciable change.

3.6 Permeability From figure 6, it can be easily seen that permeability of clayey soil is increasing gradually with increase in % of pond ash added for whole data range.

Fig. 6: Variation of Permeability with Addition of PA It changes from 9.053 × 10-6 cm/s for original soil to 1.380 × 10-5 cm/s for soil replaced with 30% pond ash. It shows almost 53% increase in the value of permeability which represents an appreciable change.

4. CONCLUSIONS Based on the experimental data collected and analysed, the soil is replaced with pond ash in four different proportions (0%, 10%, 20%, 30%). The main conclusions may be drawn as stated below: 1. The specific gravity of the soil used is 2.627 and has been classified as Cl (Silty clay of low compressibility) with LL, PL, PI, OMC and MDD are 32.8, 24.63, 8.37, 18.6% and 1.72 g/cc respectively.

[319] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 2. The value of soaked CBR and permeability for original soil obtained experimentally are 5.21 and 9.053 × 10-6 cm/s respectively. 3. The value of OMC is 18.6% which is increased up to a limit till 20% addition of pond ash after that it decreases and the MDD of original soil is 1.72 g/cc which follows reverse trend i.e. firstly decreasing till 20% addition of pond ash after that increasing with increase in % of pond ash added. 4. The experimentally obtained soaked CBR values shows a continuous increasing trend which is 5.21 for original soil and 11.72 for the soil replaced with 30% pond ash which is 125% more as compared to original soil. 5. The value of coefficient of permeability also shows a continuous increasing trend which is 9.053 × 10-6 cm/s for original soil and 1.380 × 10-5 cm/s for soil mixed with 30% pond ash which is 53% more as compared to original soil. The analysis shows that the rate of increase in CBR value is more as compared to the rate of increase in value of permeability by stabilising the soil with pond ash which results in a better subgrade material.

5. FUTURE SCOPE OF STUDY Based on the detailed discussions as mentioned above, the addition of pond ash into the clayey soil shows significant increase in the properties of original soil. Hence, this study may further be extended to calculate below given parameters: 1. The effect of different percentages of additives beyond 30% may be studied. 2. Study may be further extended for improving the drainage properties. 3. The effect of these additives can also be studied for any other type of soils.

REFERENCES [1] Bera A.K, “Effect of pond ash content on engineering properties of fine grained soil”, Indian geotechnical conference, December 16-18, 2010. [2] Chandel A.S. and Kumar U., “Permeability characteristics of clayey soil added with fly ash”, International conference of emerging trends in civil engineering (ICETCE) (October 2016). [3] Chand S.K. and Subbarao C., “Strength and slake durability of lime stabilized pond ash”, Journal of material in civil engineering, Volume 19, Issue 7 (2007) pp. 601-608. [4] Chandel A.S. and Kumar U., “Utilisation of fly ash and coir geo nets in improving the geotechnical properties of clayey soil”, International journal of engineering research & technology (IJERT) ISSN: 2278-0181, Volume 6, Issue 5, (May 2017). [5] Degirmenci N., Okucu A. and Turabi A., “Application of phosphogypsum in soil stabilization”, Science direct, Volume 42 (2007), pp. 3393-3398. [6] Ghosh A., “Compaction characteristics and bearing ratio of pond ash stabilized with lime and phosphogypsum”, Journals of materials in civil engineering (April 2010). [7] IS 2720 Methods of Test for Soils: Part 5 - Determination of Liquid and Plastic Limit, India, (1985) [8] IS 2720 Methods of Test for Soils: Part 3 - Determination of Specific Gravity/Section 1 Fine Grained Soils, India, (1980) [9] IS 2720 Methods of Test for Soils: Part 7 - Determination of Water Content-Dry Density Relation Using Light Compaction, India, 1980. [10] IS 2720 Methods of Test for Soils: Part 4 - Grain Size Analysis, India, 1985. [11] Jain P.K., Arya I.R. and Girdhar, B.S. (1995), “Use of pond ash – soil blend as subgrade material for roads and parking area of LPG bottling plant complex – A case study”, Proceedings of the National Seminar on Engineering Trends in Highway Engineering, Bangalore, pp. 32.1-32.7. [12] Jindal B.B. and Jain N., “Stabilisation of silty soil by pond ash, rice husk ash, cement and phosphogypsum”, IOSR journal of mechanical and civil engineering (IOSR-JMCE) ISSN 2278-1684, (September 2016). [13] Kumar A. and Gupta D., “Performance evaluation of cement stabilized pond ash, rice husk ash clay mixture as a highway construction material”, Journal of rock mechanics and geotechnical engineering (2017), pp. 159-169. [14] Maurya R., Kumar U. and Gupta M.K., “Hydraulic conductivity of silty soil added with plastic wastes”, International conference of emerging trends in civil engineering (ICETCE), (October 2016). [15] Maurya R., Chandel A.S. and Kumar U., “Comparative study of various soils upon addition of different materials on the basis of hydraulic conductivity parameter”, International journal of engineering research & technology (IJERT) ISSN: 2278-0181, Volume 5, Issue 5 (May 2016). [320] Sponge City: A New Concept in Urban Planning

Prof. Santosh Kumar Chairman, Indian Water Resources Society, Patna, Bihar, India

ABSTRACT The problem of urban inundation and water shortage is plaguing many world many cities due to rapid urbanization in the last few decades. Urban sprawl over the last few decades has increased impervious areas and occupied agricultural lands, forest lands, lakes, ponds, and wetlands that can store water resources. This breaks the natural water cycle that allows storm water infiltrate and replenish the groundwater storage. An urban water management program called Sponge City (SPC) was put forward in China recently in order to relieve the flood inundation and water shortage situation. Keywords: Inundation, Infiltration, Sponge City, Urbanization

1. INTRODUCTION When it rains most of storm water runoff is discharged out of the city. The most of urban flooding is caused by severe storms causing flooding of lower areas as well as flow obstructed by embanked roads and other obstacles. Urban hydrology and storm water management have been evolving to improve the urban runoff management for flood protection, public health and environmental protection over several hundred years (Fletcher et al., 2013). However, the studies focussing on storm water management has just been conducted for a few decades particularly in China followed by some more countries. The reason for considering sponge city concept is to mitigate the effects of Urban Development on natural ecosystems and solve urban-related problems at the same time (Wang et al., 2018). Some prevalent technologies applied in sponge city construction are ●● Green Roof ●● Green Spaces ●● Artificial Rainwater Wetlands, ●● Infiltration Ponds and Biological Retention Facilities, and ●● Water–Permeable Pavings Large city areas do not have the capacity of absorption, purification and filtration of rainwater leading to flooding disasters or their re-occurrence. Un-suitable urban planning strategies including poor and insufficient drainage and urban development on floodplains have created serious problems for the environment and simply increased the threat of urban flooding. For example, traditional urban drainage systems are inconsistent with urbanization and climate change, their facilities are outdated and their design standards for stormwater management have failed to adapt to urban population growth. Since it is difficult for impervious surface to infiltrate, retain and store runoff, urban areas are easy to be attacked by floods when large storm comes, threatening the safety and property of urban residents.

[321] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 2. THE SPONGE CITY The concept of Sponge City (SPC) indicates that a city can function as a sponge, whereby it absorbs, stores, infiltrates and purifies stormwater, and releases it for reuse when required. Sponge city construction aims to realise effective control and utilization of city rainwater; it is a new concept that controls rainwater based an green infrastructure.

3. PRESET STATUS Huge amount of free rainwater drop into the world’s cities each year – yet most of it is channeled straight into gutters, drains and rivers. With ever increasing urbanization many so-called ‘concrete jungles’ have cropped up. Obviously, while natural systems retain water, concrete structures tend to waste it. This results in a waste of a valuable natural resource. Climate change and rising global temperatures are making rainfall from violent storms more frequent and disastrous. These lead to devastating urban floods. Urban flooding has become a recurrent feature in Indian metros and other major cities. While cities are getting bigger and vulnerable to extreme weather events, there is no long-term vision on how to tackle such an adverse situation. With shrinking of available land, residential and commercial buildings are raised on wetlands and ponds, which were great source of infiltration and replenishment of groundwater. Thus reducing the intensity of inundation.

[322] Sponge City: A New Concept in Urban Planning 4. SOLUTION In order to address the serious problem, scientists are proposing ‘sponge cities’ when almost every drop is captured, controlled and reused. A sponge city is based on the philosophy of innovation: that a city is able to solve its water problems instead of creating them. Instead of guiding precious rainwater away, a sponge city retains it for use within its own boundaries. The water from heaven can be used in various ways - some might be used to recharge depleted aquifers, or irrigate gardens, fields and urban farms. Some could replace the drinking water we use to flush our toilets and washing etc. It could even be processed to make it clean enough to drink.

5. IMPORTANCE Sponge city is a new way of thinking about storm water not as a problem but as an opportunity and a resource to enhance our water supply volume. Associated strategies such as green space can improve quality of life, improve air quality and reduce urban heat island. Water can be used to keep spaces around verdant, and provide facility for the people working for maintenance of the area. Kitchen gardens can be used to grow food vegetables or flowers. The greatest of many advantages of sponge city is the enhanced infiltration or replenishment of groundwater, when the groundwater table is continuously declining. Another important outcome of sponge city is improvement in urban eco-system diversity as new habitats are created for a wide range of organisms. Properly implemented sponge city can reduce the frequency and severity of floods and improve water quality.

6. CHINESE EXPERIENCE According to Chinese experts the sponge city (SPC) development promotes water security, water environmental well being, ecological restoration and sustainability. The SPC programme in China was developed in the last five years. Nowhere else the idea of sponge city was embraced as enthusiastically as in China. The Chinese government is building water absorbent projects in 30-cities as part of its “sponge city initiative”. Presently the plan is to manage 60% of rainwater falling over the cities. The schemes include to develop ponds, wetlands, build permeable roads and public spaces that enable storm-water to soak into the ground. China hopes that by 2020, 80% of its urban areas will be able to absorb and re-use at least 70% of rainwater. However, transforming entire cities into sponge will require huge amount of financial support. This can only be achieved by public-private-partnership (PPP) and awareness among the people of the urgency of the matter. With rapidly growing urbanization in India and increasing urban floods, its is high time for India to move towards sponge cities.

[323] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

REFERENCES [1] MHURD (2014), Guide of sponge city construction technology based on the LID concept (Experiment) China architecture and Building Press (in Chinese), Beijing 2-7. [2] Wang W, LiJ et al. (2015/2018), Introduction of Sponge City Construction, Construction Science Technology (In Chinese 01) [3] Fletcher, T.D. et al. (2013) Understanding Managing and Modeling of Urban Hydrology, Beijing Univ. [4] https://www.researchgate.net/publication/303362681.case-studies-fo-the-sponge-city-program-in-china

[324] Modelling the Pavement Condition Assessment using Fuzzy Inference System

Madhavendra Sharma1 and Dr. S.K. Suman2 1M.Tech. Student, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Growth in the road network serves as the backbone of a developing economy. While the new roads are being constructed at high rate the in-service pavements are getting deteriorated due to different reasons. To maintain the pavements in a particular condition and serviceability, Pavement Management System (PMS) came into existence having condition rating model at the centre. The present study proposes a model to calculate the condition rating of the pavement using the Fuzzy Logic theory. The proposed model considers four of the distress parameters i.e. Rutting, Cracking, Ravelling and Potholes while providing Fuzzy Pavement Surface Rating (FPSR) as output. The model was compared with the IRC 82: 2015 method of rating the pavements. The model output was found significant with the Pearson Correlation Coefficient (R) equal to 0.74 and Mean Absolute Error (MAE) equal to 0.24. Keywords: Pavement Condition Assessment, Flexible Pavement, Distresses, Fuzzy Logic, Pavement Rating

1. INTRODUCTION The transportation infrastructure play a vital role in the growth of a country. The importance of transportation increases manifold in case of a developing country like India. At the heart of transportation infrastructure lies the road network which serves the basic purpose of connecting different places of both economic and tourism importance. India has seen a tremendous growth in road network in the previous decade and currently boasts of having the second largest road network in world. India have seen a Compound Annual Growth Rate (CAGR) of 3.52% in road lengths while a CAGR of 21.52% is observed in the investments made in road sector in the period of 2001–15 [1]. As the infrastructure is being developed at high rate, the deterioration of existing and in-service roads is also being observed. Deterioration of in-service roads is an inevitable phenomenon which cannot be neglected or avoided. Hence there is a need to maintain the existing in service roads at a particular level of service and condition. The ability to maintain an in-service pavement structure in acceptable condition, from the structural and functional points of view, is related to many factors that are often not explicit and change with time [2]. The concept of Pavement Management System (PMS) was put forward in the mid 1960’s for the evaluation and maintenance of deteriorating pavements within the constraints of available funds [3]. PMS assess the condition of pavement and suggests the treatment needs on the basis of observed condition of pavement. In order to assess the present pavement condition, different Indices have been proposed and used widely. These indices include International Roughness Index (IRI), Pavement Condition Index (PCI), Pavement Condition Rating (PCR), and Present Serviceability Index (PSI). Each and every one of these indices listed above, concerns different quantitative and qualitative characteristics of pavement conditions and provides a quantitative index that represents the present pavement condition [4], [5]. As per the Indian guidelines the rating of existing pavement is done on the scale of 1–3, where 1 corresponds to Poor and 3 corresponds to Good pavement. The rating is done on the basis of visual surveys and range

[325] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) of distresses observed on the pavement surface [6]. Visual inspections done by personnel often results in subjectivity and inconsistency while evaluating pavement distresses. Development of an expert system to categorize the distress manifestations will lend consistency to the process and minimize subjectivity [7]. Expert systems which can process information in qualitative grades (e.g. Low, medium etc.) can be developed using fuzzy logic [8], [9]. Expert systems are computer programs that depend more on heuristics of experts rather than logical problem solving procedures and can eliminate the inconsistency, minimize the subjectivity, and deal with uncertainty in any decision process [10]. The objective of the present study is to present a model for estimation of Pavement Surface Rating using the extent of pavement distresses. As the pavement rating systems include visual survey resulting in inconsistency the proposed model make use of fuzzy logic to deal with vagueness. Previous works done by researchers in PMS using fuzzy logic include development of Unified Pavement Distress Index for flexible pavements [11], Evaluation of flexible pavements [10], [12], [13], Prioritization of sections for maintenance and rehabilitation [14]–[16] and pavement performance modelling [17]–[19].

2. FUNDAMENTALS OF FUZZY LOGIC AND FUZZY INFERENCE SYSTEM Fuzzy Logic (FL) is a modelling approach whose work has shown to be closer to the way of human thinking. It has the ability to deal with uncertainty, ambiguity and subjectivity [13]. The modelled fuzzy logic system is often known as Fuzzy Inference System (FIS). Basic elements of a FIS are as shown in figure 1.

Fig. 1: Fuzzy Inference System [13] Often crisp values are used input data, Fuzzification converts the crisp input values into fuzzy values using the defined membership functions. Fuzzy Inference Engine consists of rules modelled in form of binary

[326] Modelling the Pavement Condition Assessment using Fuzzy Inference System logic as “If- Then” rules which converts provides the fuzzy output on the basis of fuzzy rule base. Finally the defuzzification converts the fuzzy output into a crisp output.

Fig. 2: Proposed Fuzzy Inference System for Fuzzy Pavement Surface Rating

3. METHODOLOGY The current study presents a model estimating the Fuzzy Pavement Surface Rating (FPSR) from the extent values of different surface distresses considered. The model was developed using MATLAB. The distresses considered in the model include Cracking, Ravelling, Potholes and Rutting as represented in figure 2. The Membership Functions for input and output functions were decided with due consideration to IRC 82–2015 and the same are shown in figure 3 and figure 4. For input variables triangular and trapezoidal membership functions were considered, while for output, triangular membership functions were considered in the study.

Fig. 3: Membership Functions for Input Variables

[327] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 4: Membership Function for Output Variable The next step is to form the if-then rules base. For the current study a panel of expert having three members; a professor having expertise in PMS and two industrial consultants working in the field of PMS was consulted for rules formation. There were a total of twenty-five rules modelled as shown in appendix. The developed model was used to obtain Fuzzy Pavement Surface Ratings (FPSR) for a dataset consisting of distress extent data for 30 sections of 1 km each. The dataset was acquired from the data repository of Civil Engineering Department, National Institute of Technology – Patna. The acquired dataset pertains to a pavement evaluation survey conducted in the year 2011–12 in the vicinity of Patna district in Bihar.

4. RESULTS AND DISCUSSIONS The application of developed model was checked in the study with the acquired dataset of pavement distress data. The acquired dataset and the ratings inferred using the developed model is represented in table 1. Condition rating of the sections was also done using the IRC: 82–2015 method and the observed ratings are represented in table 1. Relation between the condition ratings obtained from two methods is shown in figure 6. The Pearson Correlation (R) between two condition ratings was observed to be 0.74 representing a significant correlation between two condition rating methodologies and the results obtained from two. Further the Mean Absolute Error (MAE) between two condition ratings was found to be 0.24 with maximum absolute error being 0.89. MAE of 0.24 falls under 8% of the Maximum Possible Error i.e. 3 hence the developed model can be said to provide significant results. MAE can be improved by inclusion of more rules in the rule base and increasing the number of experts consulted which could result in more consistent and significant results.

Fig. 5: Performance of Developed FIS with Respect to IRC Method

[328] Modelling the Pavement Condition Assessment using Fuzzy Inference System

Table 1: Acquired Dataset and Rating Results Section IRC IRC FPSR Rutting Ravelling Cracking Pothole FPSR ID Rating Condition Condition 1 7.75 1.35 18.76 0.00 1.65 Fair 1.98 Fair 2 11.70 5.13 12.87 0.00 1.41 Fair 1.79 Fair 3 3.72 5.98 8.30 0.13 1.80 Fair 1.68 Fair 4 3.30 0.84 11.58 0.00 2.17 Good 2.12 Good 5 2.67 5.58 0.18 0.07 2.45 Good 2.69 Good 6 0.35 11.37 8.28 2.35 1.64 Fair 1.50 Fair 7 7.20 3.90 3.90 0.07 2.11 Good 2.67 Good 8 6.07 2.22 0.76 0.00 2.32 Good 2.93 Good 9 2.76 6.78 2.52 3.20 2.06 Good 1.50 Fair 10 0.25 0.00 1.35 0.02 2.94 Good 2.87 Good 11 2.79 0.65 3.50 0.08 2.70 Good 2.61 Good 12 2.35 0.00 5.16 0.16 2.33 Good 2.78 Good 13 10.35 11.37 9.84 1.20 1.00 Poor 0.92 Poor 14 1.10 1.66 3.00 0.15 2.52 Good 2.70 Good 15 9.52 5.72 4.00 0.02 1.95 Fair 2.84 Good 16 1.95 2.00 0.37 0.02 2.57 Good 2.82 Good 17 9.20 13.73 19.16 3.65 1.08 Fair 1.50 Fair 18 6.70 0.00 4.96 0.13 2.42 Good 1.98 Fair 19 2.17 4.69 7.08 0.15 1.94 Fair 2.79 Good 20 0.83 1.30 0.50 0.00 2.66 Good 2.93 Good 21 9.42 1.34 12.61 0.15 1.51 Fair 1.76 Fair 22 2.15 2.19 3.64 0.02 2.46 Good 2.78 Good 23 2.24 1.20 2.13 0.08 2.50 Good 2.58 Good 24 4.30 0.28 0.62 0.00 2.72 Good 2.84 Good 25 9.48 7.92 4.92 0.05 1.87 Fair 2.76 Good 26 5.38 8.42 3.04 0.03 2.16 Good 2.70 Good 27 9.82 6.55 4.75 0.08 1.87 Fair 2.63 Good 28 1.96 1.17 15.76 0.10 1.96 Fair 1.80 Fair 29 2.44 0.00 3.29 0.07 2.74 Good 2.66 Good 30 7.88 4.93 1.20 0.12 2.11 Good 2.88 Good Although differences were observed in the two condition rating methods. But the sections were found to be in the same condition category derived on the basis of rating values with outliers in three cases. Which corresponds to 10% of the number of sections considered which can be attributed to the data properties and the rule base modelled in the FIS. The difference observed also signifies the difference in the two approaches of condition rating and the perceptions of the experts consulted.

5. CONCLUSION A Fuzzy Inference System based Pavement Condition Rating system was developed in the study and the model was tested against a dataset containing pavement distress data. Main conclusion from the present study can be summarised as follows:

[329] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) ●● FIS based pavement condition rating model can be implemented to compensate the subjectivity and vagueness involved in the evaluation process. ●● Developed FIS based model was found to be significant with the IRC 82 method with R = 0.74 and MAE = 0.24. ●● For a better fit and improved MAE value the model can be modified with consulting a larger panel of experts.

ACKNOWLEDGEMENT The authors would like to present their gratitude towards the member of expert’s panel consulted during rule base formation.

REFERENCES [1] Morth, “Basic Road Statistics 2015-16,” New Delhi, 2015. [2] A. Bianchini, “Fuzzy Representation of Pavement Condition for Efficient Pavement Management,” Comput. Civ. Infrastruct. Eng., vol. 27, no. 8, pp. 608–619, 2012. [3] T. Karan, M.A., Haas, R. and Walker, “Illustration of pavement management: From data inventory to priority analysis.,” Transp. Res. Rec. (814)., pp. 22–28, 1981. [4] M.Y. Shahin, Pavement Management for Airports, Roads and Parking Lots. Springer US, 2005. [5] K. A. Zimmerman, “Pavement Management Methodologies to Select Projects and Recomment Preservation Treatments,” Washington D.C., 1995. [6] IRC 82 -2015, “Code of practice for maintenance of bituminous surfaces of highways,” 2015. [7] S. Labi and K. C. Sinha, “Life-Cycle Evaluation of Flexible Pavement Preventive Maintenance,” J. Transp. Eng., vol. 131, no. 10, pp. 744–751, 2005. [8] Z. Li, C.K. Chau, and X. Zhou, “Accelerated Assessment and Fuzzy Evaluation of Concrete Durability,” J. Mater. Civ. Eng., vol. 17, no. 3, pp. 257–263, 2005. [9] S. K. Suman and S. Sinha, “Pavement Maintenance Treatment Selection Using Fuzzy Logic Inference System,” vol. 2, no. 6, pp. 172–175, 2012. [10] H. K. Koduru, F. Xiao, S. N. Amirkhanian, and C. H. Juang, “Using Fuzzy Logic and Expert System Approaches in Evaluating Flexible Pavement Distress: Case Study,” J. Transp. Eng., vol. 136, no. 2, pp. 149–157, 2010. [11] C. H. Juang and S. N. Amirkhanian, “Unified Pavement Distress Index for Managing Flexible Pavements,” J. Transp. Eng., vol. 118, no. 5, pp. 686–699, 2007. [12] M. Gunaratne, J. L. Chameau, and A. G. Altschaeffl, “A successive fuzzification technique and its application to pavement evaluation,” Civ. Eng. Syst., vol. 5, no. 2, pp. 77–80, 1988. [13] A.H.A. Al-haddad and I. S. J. Al-haydari, “Modeling of Flexible Pavement Serviceability Based on the Fuzzy Logic Theory,” vol. 6433, no. Astm 2016, pp. 1–10, 2018. [14] A.P. Singh, A. Sharma, R. Mishra, M. Wagle, and A. K. Sarkar, “Pavement condition assessment using soft computing techniques,” Int. J. Pavement Res. Technol., vol. 11, no. 6, pp. 564–581, 2018. [15] A.K. Sandra, V. R. Vinayaka Rao, K. S. Raju, and A. K. Sarkar, “Prioritization of pavement stretches using fuzzy MCDM approach - A case study,” Adv. Soft Comput., vol. 39, no. 1999, pp. 265–278, 2007. [16] J. Farhan and T. F. Fwa, “Use of Fuzzy Analytic Hierarchy Process in Pavement Maintenance Planning,” 2010. [17] B. S. Mathew and K. P. Isaac, “Development of Probabilistic Deterioration Models and Prioritisation of Low Volume Roads for Maintenance,” Int. J. Traffic Transp. Eng., vol. 7, no. 2, pp. 216–231, 2017. [18] M. Terzi, Serdal, Morova, Nihat, Karasahin, “Determining of Flexible Pavement Condition Rating Deduct Value with Fuzzy Logic Algorithm.” [19] N. F. Pan, C. H. Ko, M. Der Yang, and K. C. Hsu, “Pavement performance prediction through fuzzy regression,” Expert Syst. Appl., vol. 38, no. 8, pp. 10010–10017, 2011.

[330] Modelling the Pavement Condition Assessment using Fuzzy Inference System APPENDIX

Table 2: Rule base Formed for Fuzzy Inference System Rule No. If “Cracking” is And “Ravelling” is And “Potholes” are And “Rutting” is Then 1 Low Low High Low Fair 2 Low Low Low Medium Fair 3 High Low Medium Medium Fair 4 Medium Medium Low Medium Fair 5 High Medium Medium Medium Fair 6 Medium High Low Medium Fair 7 Medium High Medium Medium Fair 8 Low High Low Medium Fair 9 Low Low Medium High Fair 10 Low Low Low Low Good 11 Low Low Medium Low Good 12 Medium Low Medium Low Good 13 Low Medium Medium Low Good 14 Medium Medium Low Low Good 15 High Medium High Low Poor 16 Low High High Low Poor 17 High High Low Low Poor 18 High Low High Medium Poor 19 High High High Low Poor 20 Low High High High Poor 21 Medium High Medium High Poor 22 Medium High High High Poor 23 High High Low High Poor 24 High High Medium High Poor 25 High High High High Poor

[331] Evaluation of Cement Treated CMSDBC with Rapid Setting Bitumen Emulsion

Rajnikant Verma1 and S.K. Suman2 1M.Tech Student, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Hot Mix Asphalt (HMA) is used predominantly as a road surface mix from many decades in road construction. In India about 90 percent road network is constructed of bituminous only. Certain limitations are associated with the use of HMA such as emission of greenhouse gases from hot mix plant, running off of plants during rainy season, problems in maintaining the road surface temperature when hauling distance from plant is more. This study presents the mix design of cold mixes for use in semi dense bituminous concrete. Semi dense bituminous concrete is mix proportion of coarse aggregate, fine aggregate and filler mixed with different content of bitumen emulsion. Test conducted on CMSDBC mix are Marshall Stability test and Tensile strength test. Cement is used as filler in the mix as cement plays the predominant role in both early stage and final strength of the mix. Bitumen emulsion also plays the predominant role in both early stage and final strength. However adhesion between mortars of mix in early stage but the cohesion in emulsion cement mortar provides the strength of the mix after curing.

1. INTRODUCTION For the last four decades the constructions of bituminous pavements using hot mixes have been most commonly adopted by the road construction agencies in India. Cold mixes roads are playing vital role in better mobility, communication, social development and economic growth of our country. But due to oil crisis in 1973, the cost of bitumen has increased and shortage of energy have caused tremendous rise in the cost of production of hot mixes and cost of construction of road with these mixes in addition to the increased cost, the concern about the environmental protection from pollution may not allow to continue the use of hot mixes for road constructions. Bitumen emulsion acts as an appropriate alternative of bitumen for construction of road due to elimination of heating of binder and aggregates. Before its extensive use as a substitute of bitumen the cold mix technology in its present scenario in the country need to be upgraded by undertaking laboratory studies and field trials. A cold mix is defined as a mixture of bitumen emulsion and aggregate that is mixed together at room temperature. Bitumen emulsion being liquid at room temperature, there is no need to heat or dry the mineral aggregate. Several benefits are gained from using cold mix asphalt (CMA) instead of hot mix asphalt (HMA). These benefits include conservation of materials and energy, preservation of the environment and reduction in cost. One of the common types of CMA is cold bitumen emulsion mixture (CBEM). Although the advantages of CMAs are real, they attract relatively little attention and are considered inferior to HMA as structural layers due to their less satisfactory performance. This may be at least partially due to the wide variation in available mix design procedures, tests and criteria. Some authorities and researchers have proposed mix design procedures, based on empirical formulae, laboratory tests or past experience. However, there is no global agreement on mixture design method or structural design methodology for CMAs. Thus, it is clear that optimization of mixture parameters has to be made more structural layers [332] Evaluation of Cement Treated CMSDBC with Rapid Setting Bitumen Emulsion due to their less satisfactory performance. This may be at least partially due to the wide variation in available mix design procedures, tests and criteria. Some authorities and researchers have proposed mix design procedures, based on empirical formulae, laboratory tests or past experience. However, there is no global agreement on mixture design method or structural design methodology for CMAs. Thus, it is clear that optimization of mixture parameters has to be made more consistent in order to promote the technology whereas the variations in material proportions will generate differences in performance. It is therefore essential to design and optimize mixture components in order to achieve appropriate properties. Cold mix is useful in the areas, where there is requirement of long hauling distance between the job sites and the plant site. This technology is becoming more attractive due to awareness about environmental protection. It is used in surface treatment, patching material, pothole filling and road maintenances. It can also be used as surface course or base course. Cold mix is used in bituminous base (BM), binder course (BM/SDBC) as well as wearing course (SDBC) of flexible pavement. Semi dense bituminous concrete (SDBC) is a continuously graded mix, which can be used as binder course or wearing course in flexible pavements. Cold dense semi dense bituminous concrete consists of coarse aggregate, fine aggregate and filler in suitable proportion mixed with sufficient quantity of mixing water and cationic bitumen emulsion. In this section filler is used as Portland cement. The effect of cement as an additive was examined in various fields. It can increase the initial stiffness, decrease the permanent deformations.

1.1 Objectives 1. To determine the physical and chemical properties of bitumen emulsion. 2. To determine the Marshall stability parameters for cold mixed SDBC using cement as filler. 3. To determine the indirect tensile strength for cold mixed SDBC using cement as filler.

1.2 Scope Cold mix technology is used in large volume of maintenance of roads. It can be used to make pavement in emergency conditions. It is used in surface treatment, patching material, pothole filling and paving maintenance applications in short period of time. Cold mix reduces pollution. Cold mix technology can be used to investigate the surface coarse material for low volume roads. Cold mix technology minimizes cost of construction.

2. LITERATURE REVIEW Various researches have been done in the field of cold mix technology using cement fly ash and rice husk ash. Researcher found so many results in the field of cold mix technology using cement and other materials. Optimizing the mix design of cold bitumen emulsion mixtures using response surface methodology” and concluded that Cold mix asphalt (CMA) has been increasingly recognized as an important alternative worldwide. One of the common types of CMA is cold bitumen emulsion mixture (CBEM). In the present study, the optimization of CBEM has been investigated, to determine the optimum proportions to gain suitable levels of both mechanical and volumetric properties. The results indicate that the interaction of BEC (Bitumen Emulsion Content), PWC (Pre-wetting Water Content) and CT (Curing Time) influences the mechanical properties of CBEM (Ahmed I. Nasser et al.,). However, the PWC tended to influence the volumetric properties more significantly than BEC. The individual effects of BEC and PWC are important, rather than simply total fluid content which is used in conventional mix design method. Also, the results show only limited variation in optimum mix design proportions (BEC and PWC) over a range of CT from 100 to 300. The variation range for optimum BEC was 0.42% and 0.20% for PWC. Furthermore,

[333] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) the experimental results for the optimum mix design were corresponded well with model predictions. It was concluded that optimization using RSM is an effective approach for mix design of CBEMs. Analyzed the paper on effect of copper slag and recycled concrete aggregate on the properties of CIR mixes with bitumen emulsion, rice husk, Portland cement and fly ash. He observed that CIR mixture containing CS and Portland cement has the highest Marshall Stability and MQ values (Ali Boyhood et al.,). The lowest Marshall stability and MQ values were obtained for the mixture containing RCA and without additive. The study on Coal waste application in recycled asphalt mixtures with bitumen emulsion and concluded that the results showed that utilizing coal waste and its ash improved the mechanical properties by increasing the Marshall stability, tensile strength and resilient modulus particularly in the long-term. These improvements were more obvious for coal waste ash because of its higher pozzolanic features. Coal waste ash improved resistance against moisture damages meanwhile; coal waste could not exert a positive effect on moisture sensitivity. The use of lime as a complement for coal waste and its ash resulted in development of semi- cementations materials and increased the stiffness of recycled emulsion and cement (CRME) are firstly studied, and then the direct tensile test is used to determine the early-stage strength development law of emulsion asphalt–cement mortar. Lastly, the image analysis is used to identify the fracture morphology of cross-section of cold recycled mixture, and the development mechanism of cold recycled mixture is revealed (Amir Modarres and Pooyan Ayar). The results indicate that the cement plays the predominant role in strength of CRME in first 3 days, while emulsion asphalt plays the predominant role in both early- stage and final strength. Moreover, the adhesion between mortar and aggregate provide the strength for CRME in earth-stage, while the cohesion in emulsion–cement mortar mixture. In addition, the findings of toxicity characteristic leaching procedure test showed that the amount of heavy metals in leach ate from mixtures containing coal waste and its ash was lower than the standard level. Generally, the application of coal waste and its ash in recycled mixtures is regarded as a step toward environmental preservation by reducing the amounts of Accumulated waste and the lowering of construction costs compared to other additives. Study on the development mechanism of early-stage strength for cold recycled asphalt mixture. He concluded that the mechanism of early-stage strength for cold recycled asphalt mixture using emulsion asphalt can increased. Influence parameters of early-stage strength development for cold recycled mixture by providing the strength for CRME after curing (Juntao Lin et al.,). The findings in the paper provide new approaches to improve the early stage strength of CRME. Studied on the model for resilient modulus determination of recycled mixes with bitumen emulsion and cement from ITS results and found that increasing curing time and cement content and decreased temperature led to increase indirect tensile strength and resilient modulus (Kavussi et al.,). Study on the topic laboratory fatigue models for recycled mixes with bitumen emulsion and cement. He found that the addition of cement increases the resilient modulus, shear strength and permanent deformation resistance of the cold recycled mixes with bitumen emulsion (CRME) and decreases the moisture sensitivity (Moderns et al.,).

3. SELECTIONS OF MATERIALS

3.1 Coarse Aggregate Coarse aggregates are carried out from local market. It is the major constituent of sub base and base courses of flexible pavement layer. Aggregate predominantly bear the load stress happening on the pavement and also wear abrasion action of traffic movement. Therefore toughness, hardness, resistance from getting polished or smooth, good shape factors, resistance to weathering are the desirable properties of aggregates. The mix selected for this study is bituminous concrete. All standard requirement for the aggregate used for bituminous concrete are specified in ministry of road transport and highways. For this

[334] Evaluation of Cement Treated CMSDBC with Rapid Setting Bitumen Emulsion study 13mm nominal size aggregate were used for grade 2 gradation of bituminous concrete mix. The physical property of the aggregate is shown in table 1:

Table 1: Physical Properties of Coarse Aggregates Property Test Method Specification Particle size Combined index IS: 2386 (P-1) <30% Toughness Impact test IS:2386(p-1V)-1997 <30% Hardness Los Angeles abrasion test IS:2386(p-1V)-1997 <30% Strength Aggregate crushing value test IS:2386(p-1V)-1997 <30% Quality of material Water absorption test IS:2386(p-111)-1997 <2% Quality of material Specific Gravity Test IS:2386(p-111)-1997 2.50-3.2

3.2 Fine Aggregate Fine aggregates are carried out from local market. Fine aggregate are basically sands and it is formed from the land or the marine environment. Fine aggregates generally consist of natural sand or crushed stone. Sand is a naturally occurring granular material composed of finely divided rock and mineral particles. It is identified by size, being finer than gravel and coarser than silt. The average particle size is below 4.75mm.

3.3 Cement Cement is carried out from local market. Cement used in this mix is as filler. The main purpose of using cement in mix is to increased mechanical properties. Cement is a binder substance used in construction that sets, hardens and adheres to other materials binding them together.

3.4 Bitumen Emulsion Bitumen emulsion is a liquid product in which a substantial amount of bitumen is dispersed in finely divided condition in water in presence of emulsifying agent.

[335] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 1: Bitumen Emulsion source: civilblog.org Physical and chemical properties of bitumen emulsion are shown in table-2

Table 2: Physical & Chemical Properties of Emulsion

Parameter Specifications Code Residue on 600 micron IS sieve, percent by mass ,max 0.05 IS 8887:2004 ANNEX B Coagulation of emulsion at low temperature Nil IS 8887:2004 ANNEX C Particle charge Positive IS 8887:2004 ANNEX E Miscibility with water No coagulation IS 8887:2004 ANNEX H Residue by evaporation, percent ,min 60 IS 8887:2004 ANNEX J Penetration on 25 degree/100g/5sec 80-150 IS 1203-1978

4. RESULT AND DISCUSSION

4.1 Marshal Stability Test Marshall Stability test is performed on graded mix and results are calculated in graphical form.

[336] Evaluation of Cement Treated CMSDBC with Rapid Setting Bitumen Emulsion

Fig. 2: Bitumen Emulsion v/s Stability Fig. 3: Bitumen Emulsion v/s Density

Fig. 4: Bitumen Emulsion v/s Flow Fig. 5: Bitumen Emulsion v/s Percentage Air Voids

Fig. 6: Bitumen Emulsion v/s Voids Filled Fig. 7: Bitumen Emulsion v/s voids in with Emulsion Mineral Aggregate

[337] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 8: Bitumen Emulsion v/s Tensile Strength

From figure 2, 3 & 5, Optimum emulsion content = (7.5+7.2+6.9)/3=7.2 The optimum bitumen emulsion content is 7.2 %. The observed value from the test was compared with the standard value of bitumen emulsion as per IS 8887:2004

Table 7: Observed Value and Standard Value of Bitumen Emulsion Standard Value Properities Observed Value IS 8887: 2004 Residue on 600 micron IS sieve, percent by mass, max 0.04 0.05 Viscosity by saybolt furol viscometer, seconds:At 50 30 20-100 degree celcius. Particle charge Positive Positive Miscibility with water No coagulation No coagulation Residue by evaporation,percent,Min 64.5 60 Penetration 25 degree celcius/100gm/5 sec 107 80-150 Storage stability after 24h,percent,max 1.87 2 Coagulation of emulsion at low temperature Nil Nil The experimental value of bitumen emulsion is now compared with standard value given in IS-8887:2014. The obtained value comes under standard value. This value satisfies the condition of test and allows to be used in field. The Marshall Stability test performed on CMSDBC mould and the value obtained from experiment is now comparing with standard value which is given in IRC: SP: 100–2014. The experimental value and standard value are given in table no: 8 the experimental value satisfies the result which is given in IS code and tell the given mix is good and can be used in the field.

Table 8: Obtained Value and Standard Value of CMSDBC Mould Properties Obtained Value Standard Value-IRC: SP: 100-2014 Marshall stability (kg) 1272.4kg 500 kg Marshall flow (mm) 4.55 Max.8 Percent void in mixture 7.9 6-10 The Retained tensile strength performed on CMSDBC mould and the experimental value obtained from test in now comparing to the given value in IRC: SP: 100–2014. The minimum value of Retained tensile

[338] Relationship between Roughness and Pavement Distresses using ANN and Statistical Model

Rajnish Kumar1 and S.K. Suman2 1Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT The present investigation shows the relation between pavement roughness and distress parameters like potholes, raveling, cracked areas, patch work and rut depth. The pavement distresses data was gathered from the national highways in India by manual inspection. Distresses data are utilized to create linear and nonlinear regression models among roughness and distress parameters. Analysis of variance of these models showed that nonlinear regression is superior to a linear regression model.The non-linear model is also supported by R2value, root mean square value (RMSE), and mean absolute relative error (MARE). The soft computing technique such as Artificial Neural Network (ANN) is used to model the pavement roughness and distresses. The SPSS and MATLAB software tool were used to maintain the relationship between roughness and distresses parameters. The architecture of ANN is designed with 5 input value, 15 hidden nodes and one output value. The ANN network is trained with the 90 % of data set and remaining 10 % of data set is used to test the model. The result of correlation and MSE value show that ANN performed significantly in both training and testing the model. Finally, linear and non-linear regression model is compared with the performance of ANN model.The mean absolute error (MAE) value and MARE value of ANN modelare significantly lower compared to linear and non-linear regression model. Keywords: Pavement Distresses, Roughness, Artificial Neural Network, Linear and Non-linear Regression

1. INTRODUCTION Pavement surface is continuously deteriorating due to combined action of the heavy traffic load and the climatic conditions. The ability of the pavement to fulfil the demands of traffic and environmental condition is called as performance. Network-level evaluations are conducted on pavement sections within the network of pavements for which the agency is responsible, with the general purpose to document current conditions, to identify projects for maintenance, preservation and rehabilitation, to help prioritize projects and allocate budgets, and to help determine funding needs. In addition, the collection of performance data on a pavement network over time provides a valuable tool for tracking pavement performance as well as a mechanism for developing performance models that can be used to predict future conditions (both with and without the application of treatments). There are many more method to explain the pavement condition. The pavement condition index (PCI) is one of them which ranges from zero to 100. The PCI value 100 represents that the pavement is in excellent condition whereas 0 indicates the worst pavement condition. It is calculated based on the distress type, severity level and the quantity by visual inspection. The procedure provides detailed information about the each pavement section of entire project. However, PCI is a time consuming process for a city level project. To obtain a long-term pavement deterioration prediction model, a detection model of pavement deterioration starting from when it first provides service to the time it begins deterioration, as well as the annual deterioration condition during deterioration, should be established. Most time-based prediction models depend on annual structure numbers, annual equivalent standard axles, deflection resilient modulus, pavement thickness, crack level before repair, and climatic factors. The pavement condition is

[339] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) identified based on the pavement distresses. It plays very important role in the evaluation of pavement surface conditions. The pavement distresses such as cracking, rutting, potholes, ravelling and patching are observed on the most of the pavement section. These distresses cause roughness on the pavement if not treated during deterioration. The pavement roughness can have adverse effects on surface drainage which lead to negative impact on traffic safety and the pavement performance. The ability to support the current and future traffic loading is explained through structural condition whereas functional condition expressed the ability to provide a safe and smooth riding. Internationally, it is expressed as International Roughness Index (IRI) which have a major concern associated with driving quality. IRI is the most convenient index made by the visual evaluation process. IRI is different from pavement serviceability rating and s tructural number. Various methodologies and models have been developed over the years to evaluate relationship between pavement distress parameters. These approaches are based on traditional statistical approaches. Recently various groups have developed correlation analysis between IRI and pavement distress by using Artificial Neural network modelling methods and reported superior results compared to statistical modelling methods. In this an attempt has been made to develop the relationship between distress parameter and pavement performance indicator such as IRI. The objective of the present study is to develop mathematical relations between pavement distress parameters and pavement roughness using traditional statistical models (linear and nonlinear regression) and artificial neural network (ANN) model. The pavement data is collected by visual inspection of national highways in India are used to develop these models. The three models are evaluated for two highways regions individually and also for combined data. Finally, a comparison is made between the three modelling techniques based on statistical parameters.

2. LITERATURE REVIEW Liu and Herman (1996) proposed a methodology to analyze the pavement distress data by applying Fechner’s psycho-physical law. It is found that AASHTO road test data obtained in Texas, road test data from Canada, and data from the internal road roughness experiment can be organized well by the simple summation of logarithmic terms of roadway characteristic variables. For flexible pavement, the mean rut depth was introduced to characterize the transverse profile of a roadway. Hozayen and Alrukaibi (2009) developed regression relationships between aggregate raveling, pavement roughness, rutting, cracking, and pavement condition rating based on logical and statistical criteria. They considered three types of models: linear, exponential, and polynomial for relations between pavement roughness and asphalt concrete raveling. The polynomial model was found the best based on R2 value. Al-Omari and Darter (1995) found no significant correlation between the IRI and either the average rut depth (RD) or the RD standard deviation when individual pavement sections were considered. However, when the data were grouped for ranges of IRI and RD means and standard deviation were averaged over these ranges, it was found that the midpoint of IRI for these ranges correlates well with both mean RD and RD standard deviation (SD) as shown below: IRI = 57.56RD − 334.28 (1) where IRI is in units of cm=km and RD is in units of mm: IRI = 136 SD − 116.36 (2) where IRI is in units of cm=km and SD is in units of mm. They also found that as the number of transverse cracks, potholes, depressions, and swells in the section increases, the IRI increases in an approximately linear relationship. Aguiar-Moya et al. (2011) developed a mechanistic empirical IRI model using long-term pavement performance data. They considered ordinary

[340] Relationship between Roughness and Pavement Distresses using ANN and Statistical Model least square (OLS) models and two-stage least square (2SLS) models for consideration of random effects, fixedeffects, and joint random effects. They identified that the IRI model developed by considering the joint random-effects approach produces better results. Mactutis et al. (2000) also developed linear regression models between IRI and percentage cracking and average rut depth on a pavement. They considered 317 observations for model development, and the relation is presented in Eq. (3): IRI = 0.597(IRIinit) + 0.0094(fatigue%) + 0.00847(rut depth) + 0.382 R2 = 0.71 (3) where IRI = international roughness index (m=km); and rut depth is in millimeters. Similar relations are developed by Mubaraki (2009) for Saudi interurban road networks and by Choi et al. (2004) for Chinese roads using multiple linear regression analysis. Al-Mansour and Alawal (2006) developed a correlation between visual inspections and roughness measurements in pavement condition evaluations. They used a linear regression model and considered cracking (C), patching (P), number of depression (D), and raveling (RAV) parameters as an explanatory variable for IRI prediction: IRI = 2.10 + 0.00267C + 0.00553 P + 0.0195D + 0.00316RAV (4) where IRI = international roughness index; C = cracking; P = patching; and RAV = raveling. Some researchers have explored use of artificial neural networks (ANN) in pavement engineering in last few years. Roberts and Attoh-Okine (1998) used quadratic function–based ANNs for pavement roughness prediction. Quadratic function ANNs are generalized, adaptive feedforward neural networks that combine supervised and self-organized learning. Lin et al. (2003) used neural networks to develop correlations between IRI and pavement distress. They considered input variables such as road level, left and right rutting, alligator cracking, cracking, potholes, patching, bleeding, corrugation, stripping, and man-holes. A multilayer feedforward neural network with six nodes in the hidden layer was used, and a back-propagation algorithm was considered for model training. Ceylan (2002) used an ANN as a pavement structural analysis tool for the rapid and accurate prediction of critical responses and deflection profiles of flexible pavements subjected to typical highway loadings. Choi et al. (2004) used multiple linear regression (MLR) and back- propagation ANNs for modeling IRI with top layer thickness, asphalt content, the structural number of the pavement, and the equivalent number of single axle loads. They found the ANN model much superior to the MLR equation. Gupta et al. (2011) measured the structural and functional response of 18 sections of low-volume road pavements in India and used regression analysis and ANNs to develop deterioration models. Thube (2012) also used the ANN modelling technique for developing pavement deterioration models for low-volume roads. He used ten input variables related to pavement history, traffic conditions, and pavement conditions in the model. The output included total cracked area, total raveling area, rut depth progression, and roughness progression. The author suggested four unified ANN-based models for prediction of pavement distresses.

3. METHODOLOGY The main objective of pavement management research is to achieve complete systematization and automation of pavement management and detection. However, even in a developed country, part of the measurement of pavement conditions still depends on manual visual inspection, whose data should be integrated and validated with data obtained from multi-functional measuring devices. The pavement roughness is measured and distresses parameters are gathered from the field by visual inspection. The data is collected for every 100 metre pavement section. Mainly, five types of distress (such as potholes, raveling, cracked areas, patch work and rut depth) data are gathered from the field. The distress and their severity level are explained in table 1.

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Table 1: Description of Pavement Distresses and Severity Level S. No. Types of Distress Severity Description Low Depth of potholes is less than 25 mm 1 Potholes Medium Depth of potholes is more than 25 mm and less than 50 mm High Depth of the potholes is more than 50 mm The aggregate or binder has started to wear away but has not progressed Low significantly. The pavement appears only slight aged and slightly roughed The aggregate or binder has worn away and the surface texture is Medium moderately rough and pitted. Loose particles may be present and fine 2 Ravelling aggregate is partially missing. The aggregate and/or binder have worn away significantly, and the surface texture is deeply pitted and very rough. Fine aggregate is High essentially missing from the surface and pitting extends to a depth approaching one half (or more) of the coarse aggregate. Low Width of cracking is less than 3 mm 3 Cracking Medium Width of the cracking is greater than 3 mm and less than 6 mm High Width of cracking is more than 6 mm Patch has low severity distress of any type including rutting < 6 mm; Low pumping is not evident Patch has moderate severity distress of any type or rutting from 6 mm to Medium 4 Patching 12 mm; pumping is not evident. Patch has high severity distress of any type including rutting > 12 mm or High the patch has additional different patch material with in it; pumping may be evident. Low Barely noticeable, depth less than 6 mm 5 Rut depth Medium Readily noticeable, depth more than 6 mm less than 25 mm High Definite effect upon vehicle control, depth greater than 25 mm All the sections selected for the present study are undividedtwo lane sections with almost symmetricalgeometricconditions and 7.5-m width. The distress data are collected forhalf-width (one lane) of road section and are in units of m2per 3750 m2 area of the pavement. Longitudinal and transversecracks are measured inlinear meters and then converted to squaremeters by multiplying by 0.03 m. The distress parameters, such as total cracks, area of potholes, patch work, rut depth, and raveling, have been considered as input variables and the IRI value as output to develop statistical and neural network models for each highway section. Flushing, bleeding, shoving, and similar other distresses were almost negligible in all sections, and therefore these are not considered in the present study.

4. MULTIPLE LINEAR REGRESSION ANALYSIS Multiple linear regression (MLR) analysis was carried out for the data to determine the functional relationship between roughness and distress parameters. The following form of relation is assumed: IRI = a0+ a1 * RD + a2 * C + a3 * PTH + a4 * P + a5 * RAV (5) where a0 = model constant; and a1, a2, a3, a4 and a5 = coefficients of rut depth (RD), crack (C), potholes (PTH), patchwork (P) and raveling (RAV), respectively. Results of analysis of variance (ANOVA) of these models are given in first part of Table 2. The t statistic indicated that area of potholes and patchwork are not significant parameters affecting the IRI for the data collected in the southern region. The t value of coefficient of these two parameters is less than critical value of 1.95 at 95% level of confidence, and p values are also higher than 0.05.

[342] Relationship between Roughness and Pavement Distresses using ANN and Statistical Model The relation between IRI and pavement distress for this region is therefore, presented in Eq. (6): IRI = 2.619 + 0.302 * RD + 0.088 * C + 0.149 * RAV R2 = 0.73 (6) A similar analysis carried out for northern region data is shown in the middle part of Table 2. Here, all coefficients are significant as indicated by their t values. The critical value of t is 1.95 at 371 degree of freedom and 95% level of confidence. Eq. (7) represents the model equation for the northern region: IRI = 2.061 + 0.436 * RD + 0.121 * C + 1.634 * PTH + 0.002 * P + 0.003 * RAV R2= 0.81 (7) where RD = rut depth (mm); C = area of total cracks (m2 per 3750 m2); P = area of patchwork (m2 per 3750 m2); PTH = area of potholes (m2 per 3750 m2); RAV = area of raveling (m2 per 3750 m2). Potholes and patchwork are not found to be significant contributors to the road roughness in the southern region data, whereas these are significant in the northern region data. It might be due to the small sample size on two highways in southern region. Further, southern and northern region data were combined and a general model as given by Eq. (8) is developed. The ANOVA of this model is shown in the right hand part of the Table 2. As may be seen, all coefficients are highly significant, as their t values are greater than the tabulated value of 1.95, and p values are also less than 0.05. IRI = 2.198 + 0.418 * RD + 0.122 * C + 0.518 * PTH + 0.002 * 0.002 + RAV R2 = 0.77 (8)

Table 2: Co-efficient for MLR Analysis Sample Size - 133 Sample Size - 377 Sample Size - 377

Parameter Coefficient t-statistics p-value Coefficient t-statistics p-value Coefficient t-statistics p-value Intercept 2.619 39.59 0.000 2.061 46.216 0.000 2.198 55.691 0.000 Rut depth (mm) 0.302 9.40 0.000 0.436 25.157 0.000 0.418 26.494 0.000 Total crack (m2) 0.088 10.30 0.000 0.121 14.459 0.000 0.122 18.910 0.000 Pothole (m2) 0.077 0.40 0.692 1.634 5.924 0.692 0.518 4.287 0.000 Patch work (m2) 0.045 1.18 0.239 0.002 15.871 0.239 0.002 15.322 0.000 Raveling (m2) 0.149 2.85 0.005 0.003 3.716 0.005 0.002 3.173 0.0016 F-test was conducted to determine if the combined model given by Eq. (8) is better than the individual models given in Eqs. (6) and (7). The results are given in Table 3. Based on individual F values, Eq. (8) is much better than Eqs. (6) and (7). For further confidence, F values of the combined model was calculated using Eq. (9):

(9) where SSR = sum of square of residuals.The Fcal was 1.134, which is less than critical value of 1.157taken from the standard table. It again emphasizes that the combinedmodel given in Eq. (8) is able to explain the data of all thefour highways significantly.

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Table 3: Results of F-test Model Equation F-value 6 71.17 7 314.8 8 338.4

5. NONLINEAR REGRESSION ANALYSIS Nonlinear regression analysis was also carried out for developingthe relation among the distress parameters and roughnessparameter. The functional form of the nonlinear models is givenin Eq. (10). The model coefficients estimated for individual dataof the southern and northern regions and also for combined dataare presented in Table 4.

IRI = a1 (RD) 1 + a2 (C) 2 + a3(PTH) 3 + a4(P) 4 + a5(R) 5 + a6 (10) α α α α α As in the case of linear analysis, the combined model was found to be better than individual models based on F test, and all coefficients a1 to a6 were statistically significant at 95% level of significance. The final model is given by Eq. (11): IRI = 0.442 (RD)0.92 + 0.092 (C)1.032 + 0.575(PTH)0.168 + 0.046 (P)0.539+ 0.174(R)0.13 + 2.01 R2 = 0.80 (11)

Table 4: Model Co-efficient by Non-linear Analysis South region North region Combined data Co-efficient N=133 t-statistics N=377 t-statistics N=510 t-statistics

a1 0.544 2.594 0.508 6.248 0.442 6.465

a2 0.061 1.416 0.049 2.042 0.092 3.136

a3 0.222 1.077 0.857 4.335 0.575 5.160

a4 0.083 0.728 0.056 1.991 0.046 1.908

a5 0.337 3.113 0.122 1.830 0.174 2.902

a6 2.315 11.874 1.874 21.000 2.010 26.944

1 0.672 0.894 0.920 1.082 1.257 1.030 α2 0.275 0.334 0.168 α3 0.464 0.511 0.539 α4 0.359 0.288 0.130 α5 R2 value 0.757 0.826 0.799 α SSE 20.913 100.845 135.326 RMSE 0.396 0.517 0.515

6. ARTIFICIAL NEURAL NETWORK (ANN) An artificial neural network (ANN) is a parallel information processing system that has certain performance characteristics similar to biological neural networks. A neural net consists of a large number of simple processing elements called neurons. Each neuron is connected to other neurons by means of directed links, and each directed link has a synaptic weight associated with it. These are used to address problems that are intractable or

[344] Relationship between Roughness and Pavement Distresses using ANN and Statistical Model

Fig. 3: Structure of ANN Model Cumbersome with traditional methods. The processing ability of the network is stored in the interunit connection strengths or synaptic weights, obtained by a process of adoption to, or learning from, a set of training patterns. Fig.4 shows a simple example of an artificial neuron. Mathematically, if I1; : : : Ii : : : In are the input values and Wlj; : : : Wij, Wnj are synaptic weight values, then netj is the summation (over all the incoming neurons) of the product of the incoming neuron’s activation and the synaptic weight of the connection at the typical jth neuron expressed as P IiWij. Thresholdvalue i is incorporated into the output. θ [345] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) The process of developing BPNN model usually involves four basic stages. They are: selection of a problem domain, architecting network topology including the number of units in each input, output, and hidden layers, learning parameters and tolerance levels, and choosing a learning paradigm to train the network and evaluation of the trained network for unseen samples. In this study, multilayer feedforward neural network with a single hiddenlayer was considered, along with a back-propagation algorithm (Dayhoff 1990) for training the network. Fig. 3 presents the structure of the ANN model for modelling the roughness and pavement distress parameters. The MATLAB (2007) neural network tool box was used to train the multilayer feedforward back-propagation network.

Fig. 4: Function of Artificial Neuron

7. RESULT AND DISCUSSION

7.1 Validation of Regression Analysis Regression models developed for the combined data have been validated here using Student’s t-test and F test for comparing if there is any significant difference between observed and modeled mean IRI values and between their variances using Eqs. (12) and (13):

(12) where xa and xm = the mean values of observed and modeled IRIvalues, respectively; and = their variances; and Na and Nm =their sample sizes, respectively. For the F test we have

(13) where and = the larger and smaller of two sample variances ofobserved and modeled IRI value.

[346] Relationship between Roughness and Pavement Distresses using ANN and Statistical Model

Observed IRI (m/km) – . – Line at 45 degree

Fig. 5: Validation of Combined Model to Southern Region Data The models developed for the combined data [Eqs. (8) and (11)]are used to predict the roughness on southernregion, and these predicted values of IRI are compared with actualobserved values in Fig. 5. A paired t test was used to see if therewas any significant difference between observed and estimated IRIvalues. The t value in both the cases was lower than tabulated value[calculated t was 1.36 for Fig. 3(a) and 1.32 for Fig. 3(b) against thetabular value of 1.96]. F-value is also in both the cases was lowerthan critical value [calculated F was 1.31 for Fig. 3(a) and 1.21 for Fig. 3(b) against the tabular value of 1.506]. These tests suggestthat the model Eqs. (8) and (11) are able to predict the roughnesson southern region correctly.

8. PERFORMANCE OF ANN MODEL Out of 510 observation records, 459 (90%) were considered for model training and the remaining 10% for model testing. One thousand iterations were performed to train the network. Figs. 6 (a and b) show the BPNN model performance in training and testing phase, respectively. The goodness of fit values are estimated in terms of R2 and MSE. The R2 value is 0.86 during training and 0.76 during testing. MSE values during training and testing phases are 0.22 and 0.43, respectively. These results show that neural network model performed highly significantly in both training and testing phases. In order to further investigate the BPNN model applicability, a separate model is developed by considering the North region highway distress data (377 sample data). The same optimum topology as discussed above (five input nodes, 15 hidden nodes, and one output node) is considered in network training, and a threshold of 0.001 MSE is considered to stop the training process. After training, themodel is tested for the southern region data(133 samples) formodel transferability to a different region. The MSE values duringtraining and testing phase were obtained as 0.25 and 0.431, andR2 values were 0.835 and 0.65, respectively. Higher coefficientsofdetermination observed during training, as in the case ofmodel development for total data (R2=0.86), indicate that theBPNN model efficiently maps the relation among IRI and distressparameters, even if the sample data size is reduced. The MSEvalues obtained during training and testing are also small (less than0.50), emphasising that the developed BPNN model is able to fitthe regional data and can be used for any highway data which isunseen to the model. This explains that the difference between theactual observation and the response predicted by the model isinsignificant.

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Fig. 6: Observed and Estimated IRI for Combined Data

9. EVALUATION OF REGRESSION AND NEURAL NETWORK MODELS Neural network and regression models are evaluated for the combined data. For more objective evaluation, a range of conventional measures such as mean absolute error (MAE), root mean squared error (RMSE), and mean absolute relative error (MARE) are estimated for the entire model and presented in Table 5. Theseterms are defined as follows:

(14)

(15)

(16) where = observed IRI value; and = estimated IRI value from the neural network or the regression model. [348] Relationship between Roughness and Pavement Distresses using ANN and Statistical Model

Table 5: Performance Evaluation of Regression and ANN Models S. No. Model (Sample Size – 510) MAE RMSE MARE (%) 1 Multiple linear regression (MLR) 0.467 0.550 16.0 2 Nonlinear regression 0.435 0.515 14.6 3 Artificial Neural Network (ANN) 0.387 0.469 12.6 Various absolute and relative measures of predicting accuracy are shown in Table 5 for all the three models. The mean absolute error (MAE) for ANN model is 0.387, which is almost 18% less than that in multiple linear regression analysis and around 11% less than that in nonlinear analysis. MARE values are also low in the case of neural network models (12.6%). Considering these measures of predicting accuracy, it is concluded that the ANN model yields better forecast of road roughness for the given pavement distresses. Also, as the number of the explanatory variables increases, the prediction capability of regression models marginally decreases.

10. CONCLUSIONS The following conclusions of this studies are as: ●● The ANOVA resultsof linear regression analysis indicate that pot holes and raveling arenot as highly correlated with pavement roughness as rut depth,total cracked area, and patchwork, but the t-statistic values of thesetwo parameters are also greater than critical value of 1.95, emphasisingthat these parameters are also significant in estimating thepavement roughness. ●● Similarly, in the case of nonlinear regressionmodel, raveling is found to be more significant (t-value is 26.94)as compared to other four distress parameters. The nonlinear relationis found better than linear model based on R2, RMSE, andMARE values. ●● The performance of regression modelsdecreases as the number of model parameters increases becausethese models are unable to map complex relation between dependentand independent variables.The ANN, on the other hand, iscapable of modelling the complex relations between the variablesbecause it is a distribution free model and does not involve anyassumption of linear or nonlinear nature of parameters. ●● Potholes, total cracked area, and raveling arefound to be major contributors to road roughness, whereas rutdepth and patchwork are relatively less important distress parametersfor predicting roughness.

REFERENCES [1] Aguiar-Moya, J. P., Prozzi, J. A., and de Fortier Smit, A. (2011).“Mechanistic-empirical IRI model accounting for potential bias.”J. Transp. Eng., 137(5), 297–304. [2] Al-Mansour, A., and Alawal, R. (2006). “Correlation of visual inspectionand roughness measurement in pavement condition evaluation.” FinalResearch Report No. 424/28, College of Engineering, Research Centre,King Saud Univ., Riyadh, Saudi Arabia. [3] Al-Omari, B., and Darter, M. I. (1995). “Effect of pavement deteriorationtypes on IRI and rehabilitation.” Transportation Research Record 1505,National Research Council, Washington, DC, 57–65. [4] Ceylan, H. (2002). “Analysis and design of concrete pavement systemsusing artificial neural networks.” Ph.D. dissertation, Univ. of Illinoisat Urbana-Champaign, Urbana, IL. [5] Choi, J.-H., Adams, T. M., and Bahia, H. U. (2004). “Pavement roughnessmodeling using back-propagation neural networks.” Comput. AidedCiv. Infrastruct. Eng., 19(4), 295–303. [6] CSIR-Central Road Research Institute (CRRI). (2008). “Report on primarydata collection through network survey vehicle (NSV).” CRRI-RDM/2.10, New Delhi, India. [7] Dayhoff, E. J. (1990). Neural network architecture: An introduction,Van Nostrand Reinhold, New York.Garson, G.D. (1991). “Interpreting neural network connection weights,artificial intelligence.” AI Expert, 6(4), 47–51.

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[8] Gupta, A., Kumar, P., and Rastogi, R. (2011). “Pavement deteriorationand maintenance model for low volume roads.” Int. J. PavementRes. Technol., 4(4), 195–202. [9] Hozayen, A., and Alrukaibi, F. (2009). “Development of acceptance measuresfor long term performance of BOT highway projects.” EfficientTransport and Paving Systems, I. L. Al-Qadi, T. Sayed, N. A. Alnuaimi,and E. Masad, eds., CRC Press, London, 335–348. [10] Lin, J.-D., Yau, J.-T., and Hsiao, L.-H. (2003). “Correlation analysisbetween international roughness index (IRI) and pavement distressby neural network.” 82nd Annual Meeting (CD-ROM), TransportationResearch Board, National Research Council, Washington, DC. [11] Liu, C., and Herman, R. (1996). “New approach to roadway performanceindices.” J. Transp. Eng., 122(5), 329–336. [12] Mactutis, J. A., Sirous, H. A., and Weston, C. O. (2000). “Investigation ofrelationship between roughness and pavement surface distress based onWesTrack project.” Transportation Research Record 1699, NationalResearch Council, Washington, DC, 107–113. [13] MATLAB (2015). [Computer software]. Mathworks Inc, Natick, MA. [14] Mubaraki, M. (2009). “Predicting pavement condition deterioration forSaudi urban road network.” Geotechnical Special Publication No. 193,ASCE, Reston, VA, 56–61. [15] Roberts, C. A., and Attoh-Okine, N. O. (1998). “Comparative analysis oftwo artificial neural networks using pavement performance prediction.”Comput. Aided Civ. Infrastruct. Eng., 13(5), 339–343. [16] Rumelhart, H., Hinton, G. E., and Williams, R. J. (1986). Learninginternational representation by error propagation, in parallel distributedprocessing, MIT Press, Cambridge, MA. [17] Thube, D. T. (2012). “Artificial neural network (ANN) based pavementdeterioration models for low volume roads in India.” Int. J. PavementRes. Technol., 5(2), 115–120.

[350] Effect of Temperature Variation on Rutting and Fatigue Life of Flexible Pavement

Vishal Kumar Narnoli1 and S.K. Suman2 1Research Scholar, Department of Civil Engineering, National Institute of Technology, Patna, Bihar, India 2Assistant Professor, Department of Civil Engineering, National Institute of Technology, Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Asphalt is a viscoelastic material i.e. to say that their property bears a great dependence on time and temperature. This attribute makes pavement sensitivity toward the changing temperature. Asphalt layers are highly sensitive to the nature, duration and frequency of loading, intensity of loading i.e. axle loading and configuration, temperature of pavement, environmental conditions i.e. rain and frost, as well as tyre pressure. The pavements in real scenario are mainly subjected to traffic and environmental loadings. The present work represents the effect of changing climatic conditions on the stiffness modulus of concrete. It also highlights the necessity to include the climatic factors in pavement design and rehabilitation. For studying the effect of changing climate on bituminous layer, equation of stiffness modulus of bituminous concrete is used. The pavement surface temperature is calculated using pavement temperature prediction equation. The paper discusses the impact of changing climate on fatigue life and rutting life of pavement. The Patna is used as a study region for the current work. The limitations to current research are that it is not validated by conducting field test. To correctly incorporate climatic factors in pavement design guide, a rigorous data collection, both for pavement temperature and stiffness modulus is required. The model development should be based on new machine learning techniques.

1. INTRODUCTION Transportation sector is a crucial sector for the economy of a developing nation like India, also is an essential sector of communication, employment, commerce, development of rural areas. Continuous serviceability and connectivity of such system are very much vulnerable to extreme events of rainfall, flood, hails, snow storms etc, which have cascading effect on living beings surrounding and living beings[1-2]. Asphalt is a viscoelastic material i.e. to say that their property bears a great dependence on time and temperature. This attribute makes pavement sensitivity toward the changing temperature. Asphalt layers are highly sensitive to the nature, duration and frequency of loading, intensity of loading i.e. axle loading and configuration, temperature of pavement, environmental conditions i.e. rain and frost, as well as tyre pressure. The pavements in real scenario are mainly subjected to traffic and environmental loadings. The temperature variation and loading have direct impact on pavement structural deformation and its responses. The effect of environmental factors on pavement distress mechanism was well documented by Harvey et al. The various important factor to be considered in the environmental loadings are rainfall, sunshine, solar radiation, wind speed etc. The stiffness of asphalt which determines the structural capacity of flexible pavement is highly dependent on temperature of pavement. At low temperature the asphalt concrete undergoes thermal cracking due to brittleness of AC and at high temperature it becomes soft andundergoes permanent deformation. Harvey et al. showed that how the pavement temperature and rainfall affects the distress mechanism of flexible pavement. The report prepared by Harvey et al. concluded that the climatic region should be included in the design of pavements. The design procedure developed by National Cooperative Highway Research Program NCHRP 1–37A considers the effect of climate on pavement design along with other parameters like traffic and structural data in design and rehabilitation of pavements. The design software allows the user to select a climatic region as per the location of the pavement. The main limitation to the software is that it’s database comprises data pertaining to 5 years span only this makes it incapable of accounting for temperature variability. [351] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Climate change not only effects living organisms’ but also affects every natural and manmade structures such as lakes, wells, reservoirs, buildings, roads, bridges everything that bears a direct or indirect relation to temperature and moisture change. Many factors such as increased sea mean level, seasonal patterns, global warming, extreme events like rainfall, temperature change etc, are collectively termed as climate change. Climate stationarity assumes that the climate over a period of time does not change and its variability remains within certain limits. This simplified assumptions helps engineer to design the structures based on the average values of climatic parameters recorded for certain period of time. For structures designed to service, more than 10–15 years this assumption does not remain valid, as an extreme event can lead to premature failure. Decades of research have demonstrated that extreme events are more sensitive to climate change than average events; in fact, “a changing climate … can result in unprecedented extreme weather and climate events” (IPCC, 2012). Stiffness is a material property i.e. it depends on the stress strain curve of the material. It does not depends on the geometry of the test specimen or number of test samples. Stiffness modulus of flexible pavement which determines the structural load carrying capacity of pavement under repeated moving wheel load is a function of temperature and loading, duration of loading. Stiffness of asphalt pavement gets affected by temperature, at low temperature the stiffness increases making the possibility of brittle facture and at higher temperature asphalt softens thus reducing the stiffness. Since the stiffness shows its sensitivity to temperature hence any change in temperature will be reflected as form of distresses. Barber made first attempt to correlate the pavement temperature with meteorological data using sinusoidal function, the complexity of the model made its use difficult, later Dempsey developed the temperature prediction model (Kim, 2008) (Brown, 1997) Suggested that performance of flexible pavement is greatly influenced by two factors i.e. temperature and moisture, and that site specific temperature should be considered in the design of flexible pavement and in overlaying or strengthening of existing pavement. (Hermansson, 2002) Used finite difference approximation of heat transfer model where pavement temperature data for 8 days at 3 sites were used to develop the model, only an error of 1–2 oC was observed, drawback of proposed model is that it requires data collection from 8 a.m. (Ahmed, Rahman, Islam & Tarefder, 2015) used Finite element models (FEM) to predict pavement temperature and determine the tensile strain, the vertical and tensile strains at the bottom of asphalt layers were found to increase with the increase in temperature, which may lead to rutting and fatigue damage. (Celauro, 2004) investigated the effect of hourly temperature variation on the flexible pavement rutting and fatigue life. To predict the pavement temperature the famous equation of Barber was used and for finding the stiffness of bitumen equation developed by Ullidtz (1979) (1)

Where T is the reference temperature in OC, TR&B is the softening point by Ring and Ball test, PI is the penetration index, t is the loading time in seconds. The stiffness of bituminous mix was determined from the equation developed by Heukelom and Klomp (1964) and modified by Van Draat and Sommer (1965):

(2)

(3) n = 0.83 log10[(4X105)/ ] (4) where H equals difference between actual air void minus 0.03.

[352] Effect of Temperature Variation on Rutting and Fatigue Life of Flexible Pavement 2. METHODOLOGY

2.1 Data Collection The meteorological data is been taken from Indian Meteorological Department (IMD) for the year 1980 to 2009. Data contains yearly maximum and minimum air temperature, rainfall, sunshine hours, and relative humidity. The data has been separated in class interval of 4 years as suggested by Enhance Climate Integrated Model (ECIM).

2.2 Filling Missing Entries The data obtained from meteorological department had some of the entries missing and some of the entries were mismatching from the previous trend. To correct these entries the within –station category method was employed from various missing entry filling techniques. The appropriateness of this technique is already explained in by (Nivitha & Krishnan, 2014), here xi = missing entry air temperature

(4)

2.3 Pavement Temperature Prediction Model Then we will use pavement temperature prediction model developed by Nivitha & Krishnan, 2014 in which the pavement temperature denoted as shown in eqn 5, here Pt and At denotes average pavement and air temperature in 0C, L stands for latitude for Patna i.e. 25.6oN

Pt = -0.7147 + 1.3023At + 0.1103L (5) The pavement temperature predicted by the model is then plotted in every 5 years of time interval, the pavement temperature shows a large variation within a year and for the smoothening of the curve moving average method was used.

3. RESULTS AND DISCUSSION

3.1 Monthly Variation of Modulus

Table 1: Monthly Variation in Stiffness Modulus (MPa) Year 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Month January 4512 5059 4955 4551 4226 4512 3848 4278 4708 4486 February 3028 3210 3353 3054 3666 2754 2767 3275 3536 3783 March 1452 1830 1816 1686 1921 1777 2012 1764 2442 2207 April 1608 1113 1621 1348 1178 1348 1217 1400 1283 1309 May 2350 1478 1595 1699 1348 1699 1191 749 944 319 June 1843 1608 1491 1296 1595 1374 1504 1491 1960 1595 July 1686 1621 1712 1751 1608 1764 1738 1686 1686 1699 August 2194 2194 1895 2064 1895 1803 2025 1999 2390 1790 September 2559 2663 2520 3067 2845 3041 2637 2637 2989 2650 October 3822 3926 3848 4135 4343 4043 4382 3835 3822 3770 November 5867 5163 4629 5046 5176 5202 4916 5215 5268 5255 December 5958 5789 5463 6075 5841 5463 5372 5281 5658 5372

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3.2 Fatigue Failure Fatigue life of flexible pavement has been assessed using the fatigue Eq. 1, the modulus value for different months are shown in Table 1, allowable tensile strain at the bottom of bituminous concrete has been taken from IRC 37. In present study a simplified version of fatigue equation developed by IRC 37–2012 is used to calculate the allowable number of load repetitions for fatigue damage.

where Nf is the fatigue life in number of standard axle, is the maximum tensile strain at the bottom of bituminous concrete, MR is the modulus of bituminous concrete in MPa.

3.3 Rutting Failure

18.00 E2 = 900 16.00 E2 = 1500 E2 = 2000 14.00 E2 = 2500 12.00 E2 = 3500 10.00 8.00 6.00

Rutting Rutting Life (10*-4) 4.00 2.00 0.00 80 100 120 140 Axle Load (kN)

Where Nr is the rutting life in number of standard axle, is the maximum vertical strain at the top of subgrade. Temperature and moisture variation is the most influential parameters which affects the structural integrity of the pavement. Increase in temperature both for air and pavement due to climatic change results in premature failure of flexible pavement, since bituminous layer at the top is most vulnerable to temperature variation, leading to rutting failure of bituminous layer at elevated temperature and brittle failure at low temperature. Analysis of last 40 years meteorological data shows

[354] Effect of Temperature Variation on Rutting and Fatigue Life of Flexible Pavement

4. CONCLUSION 1. Temperature variation shows considerable influence on fatigue distresses of flexible pavement. 2. Summer season were found to accelerate the rutting failure in bituminous concrete layer, whereas fatigue failure also found to increase this may be due to softening of the bituminous concrete.

REFERENCES [1] Amro Nasr, I. Björnsson, D. Honfi, O. Larsson Ivanov, J. Johansson & E. Kjellström (2019) A review of the potential impacts of climate change on the safety and performance of bridges, Sustainable and Resilient Infrastructure, DOI: 10.1080/23789689.2019.1593003 [2] Arangi, S.R. & Dr. R.K. Jain, 2015. Review Paper on Pavement Temperature Prediction Model for Indian Climatic Condition. International Journal of Innovative Research in Advanced Engineering (IJIRAE), August, 2(8), pp. 1-9. [3] Biswas, S., Hashemian, L. & Bayat, A., 2016. Investigation on seasonal variation of thermal-induced strain in flexible pavements based on field and laboratory measurements. International Journal of Pavement Research and Technology , Volume 9, pp. 354–362. [4] Celauro, C., 2004. Influence of the Hourly Variation of Temperature on the Estimation of Fatigue Damage and Rutting in Flexible Pavement Design,. International Journal of Pavement Engineering, pp. 221-231. [5] Hermansson, A., 2002. Simulation of Asphalt Concrete(AC) Pavement Temperatures for use with FWD. Road Material and Pavement Design, 3(3), pp. 281-297. [6] Huang, Y.H., 2004. Pavement Analysis and Design. 2nd ed. Upper Saddle River, NJ: Pearson Prentice Hall. [7] IRC 37, 2012. Guidelines for the Design of Flexible Pavements, third ed. IRC 37. Indian Road Congress, New Delhi. [8] Nivitha, M.R. & Krishnan, J.M., 2014. Development of Pavement Temperature Contours for India. Journal of The Institution of Engineers (India): Series A, June, 95(2), pp. 83–90. [9] Willway, T. et al., 2008. The effect of climate change on highway pavement and how to minimize them, s.l.: Transport Research Laboratory Limited.

[355] Barriers to Accessibility of Persons with Disabilities in Urban Public Transportation System Case Study of Bhopal, Madhya Pradesh, India

Amit Kumar Bala1 and Dr. Ajay Kumar2 1Student, Department of Architecture, National Institute of Technology, Patna, Bihar, India 2Assistant Professor, Department of Architecture, National Institute of Technology, Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Our world has diverse characteristics in terms of the geography and the sustaining demography. It is seeing a phase of urbanization from the last decades and in the process, it has also observed a lot of transformations. If we look into the accessibility aspect in core urban areas of the developing countries, one can easily observe existing mobility related issues. And further if we peek into the minor sections of society such as people with disabilities, one can understand the social exclusion in such urban areas. People with disabilities are an integral part of our society. So the question arises whether they are really included in our society or are facing adverse barriers in the path of achieving any kind of success in the rapidly working urban areas. This paper talks about the various physical barriers obstructing the development of this particular segment of society in the developing countries. The scope has been set within the opportunities and barriers to accessibility of such persons in urban public transportation system. Keywords: Disabilities, Accessibility, Urban, Public Transport

1. INTRODUCTION Urbanization is the current worldwide pattern in the present-day world. The manner in which we plan our urban surroundings, frameworks, offices and administrations, can both deter and empower access, interest and incorporation into our general public. The 15% of the world’s complete populace, being a casualty of incapacity, watch the absence of openness in manufactured situations, from streets and lodging, to open structures and spaces. There is an absence of availability to essential urban administrations, for example, sanitation and water, wellbeing, instruction, transportation, crisis and debacle reaction, versatility building, and access to data and interchanges in the greater part of the creating nations on the planet. These availability constraints enormously add to the hindrances and minimization looked by people with inabilities, prompting unbalanced rates of neediness, hardship and prohibition. These hindrances likewise obstruct the acknowledgment of the 2030 Agenda for Sustainable Development objectives. Disabilities refer to any difficulties encountered to an individual using body functions, doing any activities or in participation in it (World Disability Report, 2011). It very well may be trouble in observing, hearing, discourse, development, mental impediment, psychological maladjustment, or various of it (According to Census of India). For each crippled individual, there are in any event three different individuals from the family in a roundabout way influenced by the incapacity. As the total populace builds more individuals will live in urban areas. This implies more individuals with inabilities will live in urban communities. As urban areas develop in size, we have to consider how they are assembled and their identity for and simultaneously, we have to investigate whether our urban areas are extremely comprehensive. Individuals with inabilities are youthful, old, ladies, men, and of each race and ethnicity. For a really long time urban areas have been worked without considering how physical and social obstructions influence individuals

[356] Barriers to Accessibility of Persons with Disabilities in Urban Public Transportation System Case Study of Bhopal, Madhya Pradesh, India with incapacities. On the off chance that urban areas are worked in view of openness individuals with incapacities will feel included socially. To achieve this vision, the most essential component in the process will be the ensuring of organized accessibility parameters for the persons with disability and this can be done through their efficient inclusion in the urban public transportation systems.

2. NEED FOR STUDY The World Health Organization says that 15% of the total populace lives with a weakness or incapacity. In India, 2.21% of the total population consists of people with disability (census 2011). It is expected that the number of people with disabilities will increase by 120% in the next 30 years in developing countries (WHO, 2011). Inclusive planning is not done until we are considering these people, which is lacking at present in developing countries. Even though persons with disability form over 2.68 crores of the Indian population, their needs are not kept in mind while designing physical environments – whether it is buildings, roads, public transport, civic development, parks and recreational areas etc. The same dismal scenario is repeated in cities around the world. Spatial Planning can help as an instrument for transformation. People with inabilities have an equivalent appropriate to travel and utilize open and private transportation framework with respect and autonomy. Open transportation assumes a basic job in the development of its economy. Blocked off transportation framework confines versatility, precludes opportunity from securing development and dynamic interest, for a significant part of the populace who may require open transportation. Infrastructural Development is one of the key determinants of a Nation’s headway. The Infrastructure is on a very basic level the manufactured condition, the movement system and interfacing bystander condition. Establishment Development should be “complete”, in perspective on the principles of Universal Design for instance a structure for all. It will be uninhibitedly taken pleasure in and gotten to by individuals with lessened adaptability for instance senior locals, individuals with concealed and ephemeral illnesses, women in a family way, people passing on weight and PwDs. India’s establishment issues rise not just from its inability to make palatable and gainful workplaces as has been found in the National Highways Development programs, Indian Railways expanding framework, exorbitant program for plane terminal enhancements yet also not had the ability to give obstacle free condition to people with failures (PwDs). A country’s distant system progression may make preventions to the enthusiasm of PwDs in money related, urban, and open movement.

3. AIMS AND OBJECTIVES The research paper aims to study the concept of accessibility for the persons with disabilities in an urban public transportation system. The research work emphasizes on studying the case specific examples from the secondary data collected. In the process, the work seeks to identify the indicators that can help in assessing the accessibility of the persons with disabilities in the urban public transportation systems. This will help in understanding the role of accessibility and the different types of physical and social barriers on the travel behaviour of the persons with disability in specifically urban centres in the developing country. This will again result in determining the various research gaps corresponding to the accessibility of persons with disabilities in the urban public transportation systems. The broad objectives of the research work are as follows: ●● To understand the concept of accessible urban transportation system. ●● To identify the indicators of assessment of the accessibility of the persons who are specially abled. ●● Determining the lacunas related to the accessibility of persons with disabilities in the urban public transportation system. [357] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 4. SCOPE AND LIMITATIONS This paper talks about the inclusivity of the persons with disabilities, specifically respective to the accessibility offered to them in the urban centers of the developing countries. The scope has been set up to the disabilities related to the movement. The focus of the study will be towards the accessibility indicators and the physical barriers related to the accessible urban public transportation systems. The indicators shall be solely identified on the basis of the study of the existing case studies and national standards through literature review. This paper looks at efforts undertaken in the city of Bhopal – in utilizing universal access guidelines in their BRTS bus shelters. It evaluates the design components and their impact on accessibility of the persons with disabilities.

5. METHODOLOGY

6. LITERATURE REVIEW Infrastructural progression is one of the key determinants of a Nation’s headway. The Infrastructure will be masterminded, made, regulated and executed in a reasonable manner so its favourable circumstances accomplish all sections of the general public incorporating people with diminished versatility (senior natives, people with shrouded/transitory afflictions, families with youthful kids, pregnant ladies, and so forth.) and people with handicaps (PwDs). The greater part of individuals with handicap (PWD) in India are equipped for profitable work; be that as it may, their interest is constrained for the most part because of a scope of ecological, instructive and social obstructions. For example, an individual in a wheelchair probably won’t most likely look for some kind of employment - this isn’t generally a direct result of the inability, however usually due to a physically unpleasant condition that is generally populated by out of reach transports, missing walkways, or staircases rather than slopes. There is a move in inability thinking from the restorative and philanthropy models towards social/natural model. [358] Barriers to Accessibility of Persons with Disabilities in Urban Public Transportation System Case Study of Bhopal, Madhya Pradesh, India One of the primary enactments regarding handicap related issues was American with Disabilities Act, 1990 (ADA). In UK there is Disability Discrimination Act, 1995 (DDA). India, Persons with Inabilities (Equal Opportunities, Protection of Rights and Full Participation) Act (PWD), 1995 was instituted twenty years back and in the interim, there were number of changes in the handicap part, in terms of various types of incapacities and recovery. With the segment of “The Persons with Disabilities (Equal Opportunities, Protection of Rights and Full Participation) Act, 1995”; India checking and supporting the UN Convention for Protection of Rights of Disabled Persons; broadened joint exertion and coordination between the client social affairs, NGO’s and the accessories; the future framework progress, building and region neighborhood laws, the air terminals and street and gathered foundation have set the rules of Universal Design. So as to make Indian incapacity enactment in-accordance with other dynamic inability laws as of late Privileges of Persons with Disabilities Act (RPWD), 2016 came into power from nineteenth April, 2017. This Act is in-accordance with the UN Convention of the Rights of Persons with Disabilities (UNCPRD) Treaty, which India marked and confirmed without any booking. The essential rationality of RPWD is to guarantee non-segregation, rise to circumstance, regard and pride of people having inability. In request to guarantee inclusivity and measure up to chance of crippled RPWD has referenced the jobs and obligations of various partners like government, both open and private division associations, parental figures, inability-based associations, and society on the loose. J. Bezyak, S. Sabella and R. Gattis (2017) have identified various types of physical and emotional barriers for individuals with disabilities while using the public transportation and the complementary paratransit services. Their regional scaled work supported with web-based survey used indicators like modal share at transit points and the disability status along with their employment status. Their research outcome talked about the modifications required to the physical environment and attitudinal behaviour towards the individuals with disabilities who use public transportation and complementary para-transit services. Rozana Basha (2015) worked to identify barriers arising from the bad planning and the resulting accessibility issues experienced by differently abled people in local area level for the districts of Prishtina and Prizren, Kosovo. Using primary survey and mapping the spatial characteristics of accessibility, she arrived at the general recommendations to be considered while planning inclusive public spaces. J. Babinard, W. Wang, C. R. Bennett and S. Mehndiratta (2012) studied the accessibility factor of urban transport for individuals with inabilities and restricted portability on a territorial scale in East Asia and the pacific area. Through the relative investigation they examined the execution of the availability includes in transport ventures for individuals with inabilities and restricted versatility. Kunieda and Roberts (2006) addressed the mobility and accessibility problems in the urban transportation system in developing countries and used comparative analysis method to sort the secondary data collected in order to outline inclusive transport indicators and services. If we talk about accessibility as one of the essential aspects in the vast field of physical infrastructure, there are various concerns that can be looked upon in order to create any kind of understanding about the barrier free mobility. An individual without any disability while using any transportation service would be worried about his/ her access to exercises at particular areas, the availability of affordable public transit services, ability to board and land, ease of changing modes, efficient travelling time and the most important, his/ her safe travel comfort and easiness. On the other hand, if we include the additional factors concerned with persons with disability, one can notice them in the form of the availability of accessible, economical, safe and escorted transportation system. The major fundamental concerns are related to the economic parameters, framework design parameters such as walkways, section/ways out of structure, street surface, accessible toilets and other public services. These concerns although extend up to the design of accessible vehicles, public or private, and also the personal safety. The basic classification of such barriers can be done into the categories of urban and rural areas. The urban centric barriers include the entry and exit to the typology of buildings, i.e., public, residential, commercial, etc., design of roadways, trails/side strolls, inaccessible public transportation system. The rural centric barriers are also more or less the same but the difference can be observed in terms of qualitative transportation system and relative low population dependency. [359] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) BRTS stretches out in the nine Indian urban zones isolated from Delhi, have been embraced for a hard and fast length of 359 Kms to a detriment of Rs. 33520 million under the JnNURM. Ahmadabad, Rajkot, Surat in Gujarat, Indore and Bhopal in Madhya Pradesh, Pune in Maharashtra, Jaipur in Rajasthan, and Vijayawada and Visakhapatnam in Andhra Pradesh are additionally having this transport fast travel framework. An enormous part of the urban zones will have low floor transports and accessible transport q-covers. The accessible features in the relative framework administrations and establishments incorporate transport undercarriage level at 400mm, single step invaluable for setting out and arriving by all customers, wide gateways - 1200mm, securement area for wheelchair customers, adequate turning and moving space for compactness help customers, saved seating signs, handrails and stanchions with splendid shading contrast, traveller data dynamic showcase frameworks and sound location framework, sufficient lighting and ‘stop demand’ gets, seats have swing up arm rest and transport spread at a stature of 390+ mm. In Delhi, transport q-covers are synchronized to facilitate undercarriage stature of the low floor transports and approach features. The watched pointers are inclines on the different sides, material advised tiles for individuals with vision impediment, Braille plate with course information, space for two wheel-situate customers with access picture painted on the ground, data signage, shading equalization and need seats with pictograms.

7. CASE DISCUSSION As indicated by the Harmonized Guidelines and Space principles for Barrier Free Environment for Persons with Disabilities (2016), by Ministry of Urban Development, India, there is a general classification of structure typologies that should cover all the particular openness prerequisites for people with inabilities. Urban open transportation framework goes under class 6 of Transport and correspondence space which incorporates streets, railroads, airplane terminals, seaports, dockyards, transport stations, truck terminals and cargo edifices. The key barriers to accessibility for persons with disabilities in urban public transportation system can be classified on the basis of two major aspects:

7.1 Access at Trunk Level Stations ●● Ramps to stations (slope, tactile guidance, clearance, handrails) ●● Entrances & exits, Passageway width, Tactile elements ●● Floor surface and visual & audible elements ●● Platform to bus floor gap, Seats & supports ●● Clearance at fare gates and ticket counters

7.2 Access Along Trunk Line and Feeder Line Corridors ●● Surface condition of sidewalks & paths ●● Curb ramps, bollards at intersections ●● Tactile guide ways & pedestrian crossings ●● Traffic and audio signals In Bhopal, BRTS interfaces most of the urban and peri-urban parts of the city to 82 bus shelters along 4 axial routes with the allied support of various complimentary and intermediate transit courses. Even we can infer that the character of the city is very much supported by the structure of public transportation system. In Bhopal, the names of major public spaces are defined by the names of respective bus stops, i.e., 10 no. market for 10 no. bus stop, 7 no. market for 7 no. bus stop, etc. These existing supportive courses [360] 6

BRTS courses alongside the feeder availability of the other intra-city transit services running on the major axial routes. The bus facilities in the BRTS corridor got initiated in 2013. Each bus shelter platform at the transit locations is 2.5m wide and 15m long. Pedestrian guard rails are provided between bus lanes and free moving vehicle lanes. The vital concern over safety of pedestrians and specifically the person with disabilities has been observed due to the non-operating pedestrian crossing signals. This raises questions over the 6 accessibility issues throughout the BRTS corridor. Tactile pavement can be observed in the bus shelter premises to provide accessibility opportunities to persons with disabilities but the approach to BRTSthe buscourses stops alongside has not been the considered.feeder availability A wheel of Chair the other Bound intra individual-city transit can't servi reachces to running BRTS buson the stops majorin light axial of routes.the fact The that busbarriers facilities are there in the as curbsBRTS and corridor other obstacles.got initiated in 2013. Each bus shelter Barriers toplatform Accessibility 6at ofthe Persons transit with locations Disabilities is in 2.5m Urban widePublic andTransportation 15m long. System Pedestrian Case Study guard of Bhopal, rails Madhyaare provided Pradesh, India give transportbetween facilities bus lanes to and travellers free moving from vehicl the deepe lanes. neighbourhood’s to BRTS courses alongside the feeder BRTS courses alongside the feeder availability of the other intra-city transit services running on the availabilityThe ofvital the concern other intra-city over safety transit of pedestrians services running and specifically on the major the person axial routes.with disabilities The bus facilitieshas been in the BRTS corridor gotmajor initiated axial routes. in 2013.The bus Eachfacilities bus in theshelter BRTS platformcorridor got at initiated the transit in 2013. locations Each bus shelteris 2.5m wide and observed platformdue to atthe the transitnon-operating locations ispedestrian 2.5m wide andcrossing 15m long. signals. Pedestrian This guard raises rails questionsare provided over the 15m long.accessibility Pedestrianbetween issues guard bus lanesthroughout rails and freeare movingtheprovided BRTS vehicl betweenecorridor. lanes. busTactile lanes pavement and free can moving be observed vehicle in lanes. the bus shelter premises to provide accessibility opportunities to persons with disabilities but the approach to The vital concern The over vital safety concern of over pedestrians safety of pedestrians and specifically and specifically the personthe person with with disabilities disabilities has has been been observed due to the bus non-operating stopsobserved has notdue beenpedestrianto the considered. non-operating crossing A wheelpedestrian signals. Chair crossing This Bound raisessignals. individual questionsThis raisescan't reachquestionsover tothe BRTSover accessibility the bus stops issues throughoutin light the of BRTSaccessibility the fact corridor. that issues barriers throughoutTactile are therepavement the BRTSas curbs corridor.can and be otherTa observedctile obstacles. pavement in thecan bebus observed shelter in premisesthe bus to provide shelter premises to provide accessibility opportunities to persons with disabilities but the approach to accessibility opportunitiesthe bus stops hasto notpersons been considered. with disabilities A wheel Chair but Bound the individual approach can't reachto the to BRTS bus busstops stops has not been considered. A wheelin light Chair of the factBound that barriers individual are there can’t as curbs reach and other to BRTS obstacles. bus stops in light of the fact that barriers are there as curbs and other obstacles.

Figure 1: Image showing the BRTS bus stop at Board office, Bhopal (The presence of approach ramp and Fig. 1: Image ShowingFigure 1the: Image BRTS showing Bus the BRTS Stop bus at stop Board at Board Office, office, Bhopal Bhopal (The presence (The of Presence approach ramp of and Approach Ramp and absence of curb ramps and inappropriate level difference for crossing). (Source: Primary Survey) Figureabsence 1Absence: Image of curb showing rampsof Curb theand BRTSinappropriateRamps bus andstop level atInappropriate Board difference office, for Bhopal crossing)Level (The Difference. presence(Source: ofPrimary for approach Crossing) Survey) ramp and absence of curb ramps and inappropriate level difference for crossing). (Source: Primary Survey) Source: Primary Survey

Figure 3: Low floor buses and platform but lack of temporary bridging (Source: Primary Survey)

Figure 2: Approach to ramps are not maintained (Source: Primary Survey) Figure 3: Low floor buses and platform but lack of temporary bridging (Source: Primary Survey)

Fig.Figure 2: 2:Approach Approach toto ramps Ramps are notare maintained Not Maintained (Source: Fig.Figure 3: 3:Low Low Floor floor buses Buses and and platform Platform but lack But of temporary Lack of Primary Survey) Temporary Bridging bridging (Source: Primary Survey) Source: Primary Survey

[361] Figure 2: Approach to ramps are not maintained (Source: Primary Survey) 7

nd e-Book: 2 National Conference on Recent Advances in Civil Engineering (RACE-II)

Figure 4: No defined approach points near the ramp and no signage to assist any disabled person. (Source: Primary Survey)

Figure 4: No defined approach points near the ramp and no signage to assist any disabled person. (Source: Primary Survey) Fig. 4: No Defined Approach Points Near the Ramp and No Signage to Assist any Disabled Person

Source: Primary Survey

Fig.Figure 5: Absence 5: Absence of of Zebra Zebra crossingsCrossings at the at start the of Start ramps of for Ramps pedestrian for access Pedestrian (Source: Access Primary Survey)

Source: Primary Survey

Further the physicalFigure 5: barriers Absence ofto Zebra accessibility crossings at forthe startpersons of ramps with for pedestrian disability access related (Source: to movementPrimary Survey) in the BRTS, Bhopal have been discussed in table 1 listed in annexure. Further the physical barriers to accessibility for persons with disability related to movement in the The most interesting observation that can be made is safer and brighter streets. This transformation has its BRTS, Bhopal have been discussed in table 1 listed in annexure. roots emerging from the establishment of the BRTS corridor and supportive infrastructure. The transport stops areFurther outfitted the withphysical computerized barriers to accessibilityticket candy for machine persons withwith thedisability ability related to issue to andmovement revive inkeen the cards just as issueBRTS, bar Bhopal coded have tickets. been discussed The toll indoors, table 1the listed traveller in annexure. information system with the announcement services and an available escort at most of the bus shelters do add up to the positive and user-friendly urban public transportation system. [362] Barriers to Accessibility of Persons with Disabilities in Urban Public Transportation System Case Study of Bhopal, Madhya Pradesh, India 8. CONCLUSION The accessibility related transformation for the persons with disabilities is a long run plan, yet a few suggestions must be considered from the current context. Even the government policies related to the urban planning aspect are taking into account the inclusivity of the especially abled people. This projected concept of inclusiveness can only foresee success when this segment of total nation’s population is provided with accessible urban transportation system. The case of Bhopal discovers the wide exhibit of accessibility issues in the BRTS networks all throughout the city. They are majorly due to the presence of several discussed physical barriers across the BRTS corridor. Bhopal Municipal Corporation (BMC) has been providing the smart passes to persons with disabilities ensuring them up to 75% concession in BRTS tickets. The objective was to make BRTS a safer and efficient urban public transportation system for persons with disability. This will result in increasing ridership among such people due to decreased cost of travel. These types of actions from governing urban public bodies can lead to create a frequent and affordable public modal choice amongst the people with disabilities and a gradual change in their travel behaviour in urban areas of developing countries. To wrap up what has been said above, I might want to call attention to that the barriers to accessibility for the people with disabilities are not just limited to the attitudinal and emotional factors but they are primarily developing in the form of physical barriers too. Physical barrier directly targets the accessibility opportunities of such people in urban areas which indirectly is against the right of persons with disability. If they are provided with accessible public transportation system, there will be more favourable opportunities to attain the current planning goals of inclusiveness in the developing countries.

REFERENCES [1] B. Jill, S. Scott, G. Robert, “Public transportation: An investigation of barriers for people with disabilities”, Journal of Disability Policy Studies, vol. 28(1), pp. 52–60, 2017. [2] ‘Harmonised Guidelines and Space Standards for Barrier-Free Built Environment for persons with Disability and Elderly Persons’, Ministry of Urban Development, Govt. of India, February 2016. [3] Basha R., “Disability and Public Space – Case Studies of Prishtina and Prizren”, International Journal of Contemporary Architecture “The New ARCH”, vol. 2, no. 3, pp. 54-66, 2015. [4] B. Julie, W. Wei, B. Christopher, M. Shomik, “Accessibility of urban transport for people with disabilities and limited mobility: lessons from east asia and the pacific”, TRN-44, April 2012. [5] K. Mika, R. Peter, “Inclusive access and mobility in developing countries”, TRB 2007 Annual Meeting CD-ROM, November 2006. [6] B. Geneviève, Y. Genesis, “Opening the door to social equity: local and participatory approaches to transportation planning in Montreal”, Eur. Transp. Res. Rev, vol. 9, no. 43, 2017. [7] S. Anita, “RPWD Act, 2016: Fostering a Disability-friendly Workplace in Indian Organizations”, Indian journal of Industrial Relations, vol. 53, no. 4, pp. 591-603, April 2018. [8] P. Ashok, K.P. Ashok, “The Legal Rights of the Disabled in India: A Review”, Anweshan: Journal of Education, vol. vii, no. 2, March 2018. [9] J. Thomas, S. Alka, S. Rajesh, “Strength and weakness of the guidelines of Rights of Persons with Disabilities Act, 2016 (dated January 5, 2018): With respect to the persons with neurodevelopmental disorders”, Indian Journal of Psychiatry, vol. 60, no. 3, pp. 261 -264, July-September 2018. [10] R. Gaurav, “Access audit report for New Delhi railway station”, Indian institute of Roorkee, report for Accessible India Campaign. [11] F. Veronica, “The use of gis to study transport for disabled people”, Fundación de las cajas de ahorros documento de trabajo, 2007.

[363] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) ANNEXURE Barriers to accessibility, their impact on accessibility and related observation at BRTS corridor, Bhopal

Table 9–1: Barriers to Accessibility, Their Impact on Accessibility and Related Observation at BRTS Corridor, Bhopal S. Barrier Component Impact on Accessibility Observation at BRTS, Bhopal No. Access at Trunk Level A. Stations 1. Ramps to Bus stops Crossing depth before should accommodate wheelchair users i. It is less than 1200mm wide. ramp (at least 1200mm) greater than 1:12 makes it difficult for people Not following the standard, Depending ii. Ramp slope with limited mobility. on the availability of space Inadequate mid-landing prevents wheelchair iii. Ramp mid - landing depth Not present users from resting halfway up ramp Ramp landing in front of Wheelchair users require sufficient space to iv. - ticket booth turn around in front of ticket booth. Railings along the wall can provide support No walls, but handrails are present at v. Wall adjoining ramp to people with limited mobility. And visibility some of the stops options Station entrance and exit widths should Accommodation space is less at busy 2. Station entrances and exits accommodate people in wheelchairs. stops A person in a wheelchair should be able to 3. Ticket counters reach the ticket counter to communicate with Most of the stops have attendants. the attendant. 4. Fare Gates Wheelchair users require passageways at least Passageway width next to the ticket i. Passageway width as wide as their wheelchairs in order to pass. booth is 1000mm Turnstiles are not suitable for people with ii. Fare gate configuration Flap gates are present wheelchairs and flap gates are recommended. Width of turnstiles / fare Wheel chair users should be made to turn as iii. No turnstiles gates little as possible at entrances and exits. 5. Floor surface A slippery floor will hurt all passengers. Not slippery Absence of supports makes it difficult for old 6. Seats and supports Seats are comfortable persons to move, sit down or get up. There might be a possible pinch hazard if the 7. Sliding doors Doors are inside doors slide inside. 8. Platform to Bus Floor Gap This poses a hazard for persons in wheelchairs. No temporary briding provided. Access Along Trunk B. Line and Feeder Line Corridors 1. Sidewalk and Paths The absence of poor sidewalks can directly Sidewalks are not slippery, but i. Surface condition limit the accessibility of people with approach to them is not disabled disabilities. friendly. The presence of tactile guideways can ii. Tactile Guide ways improve navigation to the stations for people Tactile guiding is present. with limited vision.

Table 9–1 (Contd.)... [364] Barriers to Accessibility of Persons with Disabilities in Urban Public Transportation System Case Study of Bhopal, Madhya Pradesh, India

...Table 9–1 (Contd.)

S. Barrier Component Impact on Accessibility Observation at BRTS, Bhopal No. 2. Intersections and crossings Curb ramps benefit all users and particularly i. Curb Ramps Absence of curb ramps. wheelchair users. Pedestrian crossing signals, including audible announcements benefit all users. Refuge ii. Pedestrian Crossings No refuge areas. areas provide a safe island for all passengers while crossing the road. Where bollards are used, adequate space Bollards are present without any iii. Bollards should be provided for wheelchair users to chains connected but the distance pass between bollards. between them is less than 1000mm.

[365] Study of Drought and its Analysis in the Sone Command Area

Gaurav Kumar1 and L.B. Roy2 1M.Tech., Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected]

ABSTRACT Drought is the most complex but the least understood of all natural hazards. It is broadly defined as “severe water shortage”. Low rainfall and fall in agriculture production has mainly caused droughts. A droughts impact constitutes losses of life, human suffering and damage to economy and environment. Droughts have been a recurring feature of the Indian climate. Therefore the study of historical droughts may help in the delineation of drought prone areas facing drought risk. Based on this mitigation plans can be formulated by the government authorities to cope with the disastrous effects of this hazard. In this present work on the Sone command area, five different metrological drought indexes, namely IMD method, standard precipitation index, reconnaissance drought index, precipitation effectiveness index and moisture adequacy index were selected mainly reflecting metrological droughts. Also an effort has been made to find out the districts facing the most severe drought conditions.

1. INTRODUCTION Drought is one of the major environmental disasters, which have been occurring in almost all climatic zones and damage to the environmental and economies of several countries has been extensive and death toll of livestock unprecedented. Drought damages are more pronounced or prominent in areas where there is a direct threat to livelihoods. Sone-command area with a population of 2.6 crore as per the figures of the 2011 census is an agricultural state, where two-third of population is engaged in agriculture and earn live hood directly from this occupation. Moreover, agriculture provides indirect employment to a large portion of population in the agro-based occupations. Thus, prosperity and well being of the people in the command area are closely linked with agriculture and allied activities. Agriculture development in the state is to a large extent depends on availability of water. Semi-arid climatic conditions in the area are characterized by erratic rainfall and successive drought years together with high rate of industrial development and successive water mining has adversely affected in population levels thereby increasing drought risk. Since there is not much scope to bring additional land under cultivation in the Sone-command area, evaluation of probable risk arising out of drought in the region would help in developing better management plans for mitigating drought impacts. Although there are several drought indices for the drought assessment but the following methods have been used for the present study.

2. IMD METHOD In this method, drought was assessed on the percentage deviation Di of rainfall from long term rainfall. The procedure is such that the excess or deficit of rainfall of the preceding time periods will be influencing the adequacy of the present time period’s rainfall in meeting the requirement for the cumulative long term mean rainfall. [366] Study of Drought and its Analysis in theSone Command Area Formula used for calculating the drought index:

(1)

Where, Pi is the mean rainfall of the respective year µ = long term mean rainfall for the entire duration of the data Percentage departure of rainfall from normal can be classified into different categories on the basis of following table.

Table 4–1: IMD Classification of Drought Percentage Departure of Rainfall (Di) Intensity of Drought > 0 No Drought 0 to - 25 Mild Drought -25 to - 50 Moderate Drought -50 to - 75 Severe Drought -75< Extreme Drought

3. STANDARD PRECIPITATION INDEX (MCKEE et al., 1993) The Standardized Precipitation Index (SPI) was developed by McKee et al. (1993). The SPI is based only on precipitation. The SPI assigns a single numeric value to the precipitation, which can be compared across regions and time scales with markedly different climates. Jain et al. (2010) reported that there are a number of indices to quantify drought using meteorological data; however, the SPI is most widely used index. SPI can be calculated at different time scales and hence can quantify water deficits of different duration. SPI was designed to show that it is possible to simultaneously experience wet conditions on one or more time scales and dry conditions at another time scale. These time scales reflect the impact of a drought on the availability of the different water resources. Soil moisture conditions respond to precipitation anomalies on a relatively short scale. Groundwater, stream flow, and reservoir storage reflect the longer-term precipitation anomalies. For these reasons, McKee et al. (1993) originally calculated the SPI for 3, 6, 12, 24, and 48 month time scales. The calculation of the index needs only precipitation record. It is computed by considering the precipitation anomaly with respect to the mean value for a given time scale, divided by its standard deviation. The precipitation is not a normal distribution, at least for time-scales less than one year. Therefore, the variable is adjusted so that the SPI is a Gaussian distribution with zero mean and unit variance. A so adjusted index allows comparing values related to different regions. Moreover, because the SPI is normalized, wet and dry climates can be monitored in the same way. The index calculation is based on the following expressions:

(2)

Where, X is the mean annual rainfall, Xi is the annual rainfall at any year, and is the standard variation.

Standard deviation for precipitation is computed as: σ

(3)

[367] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Where, N is the number of years. Drought can be classified on the basis of Standard Precipitation Index as given in the following table.

Table 4–4: SPI Classification of Drought

Class of Drought SPI Values Extremely Wet > 2.0 Very Wet 1.5 to 1.99 Moderately Wet 1.0 to 1.49 Near Normal -0.99 to 0.99 Moderately Dry -1 to -1.49 Severe Dry -1.5 to -1.99 Extremely Dry < -2

4. RECONNAISSANCE DROUGHT INDEX (TSAKIRIS, 2004) A new reconnaissance drought identification and assessment index was first presented by Tsakiris, 2004 while a more comprehensive description was presented in Tsakiris et al. (2006). The index, which is referred to as the Reconnaissance Drought Index, RDI, may be calculated by the following equations. For illustrative purposes the yearly expressions are presented first. The first expression, the initial value ( ), is presented in an aggregated form using a monthly time step and may be calculated for each month of the hydrological year or a complete year. The is usually calculated for the year i in an annual basis asα˳ follows: α˳ i = 1 to N, and j = 1 to 12 (4) in which Pij and PETij are the precipitation and potential evapotranspiration of the month j of the year i. A second expression, the normalized RDI, (RDIn) is computed using the following equation for each year, in which it is evident that the parameter is the arithmetic mean of values calculated for the N years of data. α˳

(5)

The third expression, the Standardized RDI (RDI st), is computed following similar procedure to the one that is used for the calculation of the SPI. The expression for the Standardized RDI is:

(6)

In which is the ln (i), is its arithmetic mean and is its standard deviation

Drought can be classifiedα˳ on the basis of Reconnaissance drought index as given in the Table 4.5

[368] Study of Drought and its Analysis in theSone Command Area

Table 4–5: RDI Classification of Drought

Class of Drought SPI Values Extremely Wet > 2.0 Very Wet 1.5 to 1.99 Moderately Wet 1.0 to 1.49 Near Normal -0.99 to 0.99 Moderately Dry -1 to -1.49 Severe Dry -1.5 to -1.99 Extremely Dry < -2

5. MOISTURE ADEQUACY INDEX (SUBRAMANYAM et al., 1963) It was introduced by Subramanyam et al. (1963) to characterize the agricultural drought in India. Moisture adequacy index is the ratio of actual evapotranspiration to the potential evapotranspiration, expressed in percent. It is given as under:

(7)

Where, MAI = moisture adequacy index AE = actual evapotranspiration PE = potential evapotranspiration Based on the values of moisture adequacy index, the intensity of drought can be classified as under:

Table 4–6: MAI Classification of Drought

Departure of MAI (%) below Minimum Value Intensity of Drought >10 Moderate 10-20 Large 20-30 Severe <30 Disastrous

6. METHODOLOGY Drought estimation using different methods is necessary for proper mitigation measures. Different drought indices have been used namely, IMD method, Reconnaisance drought index, Standard precipitation index and Moisture adequacy index. For the required calculation Ms Excel was used. The required input data was taken from the Indian Metrological department for last 102 years. Required input data were temperature data, evapotranspiration data and precipitation data.

7. RESULT AND DISCUSSION Drought indices were calculated for last 102 years using different methods. Sample results have been shown in the following table.

[369] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Table 1: District Wise Number of Drought Years using IMD Method District No. of No Drought Year No. of Mild Drought Year No. of Moderate Drought Year Bhojpur 56 38 7 Jehanabad 53 41 7 Patna 54 40 8 Palamu 55 33 13 Rohtas 53 38 10 Aurangabad 53 36 12 Bhabhua 46 44 11 Buxar 38 51 12 Garhawa 73 24 5 Gaya 61 32 9

Table 2: Number of Drought Years using SPI Index and RDI Index Extremely Moderately Near Moderately Severe Extremely Very Wet District Wet Wet Normal Dry Dry Dry SPI RDI SPI RDI SPI RDI SPI RDI SPI RDI SPI RDI SPI RDI Bhojpur 3 3 3 4 7 6 72 72 9 10 4 4 4 3 Jehanabad 4 2 2 3 9 8 70 74 9 9 5 4 3 2 Patna 3 3 4 3 8 7 71 75 8 3 5 6 3 5 Palamu 2 1 5 3 6 13 65 67 13 10 5 1 6 7 Rohtas 2 2 4 3 10 12 68 65 9 12 5 5 4 3 Aurangabad 2 0 5 4 8 12 69 67 11 10 4 3 3 6 Bhabhua 2 2 3 2 12 11 69 69 7 12 5 1 4 5 Buxar 3 2 2 4 9 12 74 68 6 9 4 4 4 3 Garhawa 1 1 7 1 7 11 67 74 11 8 5 3 4 4 Gaya 2 1 8 5 4 12 69 71 11 2 4 3 4 8

[370] Study of Drought and its Analysis in theSone Command Area 8. CONCLUSION Drought has been occurring in the Sone Command Area for the last one century. It is essential to come out with the most appropriate techniques to assess drought in a better way and map the mild, moderate and severe droughts. From the present study, the following conclusions are drawn: 1. For meteorological drought analysis some drought indices shows better result than others. IMD method and SPI index were found to be the one of the best methods for metrological drought index computation. 2. SPI and RDI drought index predicted almost similar and better drought condition in the study area. 3. Index of Aridity and Precipitation effectiveness index did not show good results for the drought severity as they have predicted most of the months to have no drought condition. 4. Moisture adequacy and aridity index shows similar result.

REFERENCES [1] Amatayakul, P, 1993. Drought, Meteorological Research sub-Division, Study and Research Division, Meteorological Department, Thailand. [2] Allaby M (2003) Draughts. Book, ISBN-13:7980816047932 American Meteorological Society (AMS), 2004. Statement on meteorological drought. Bull.Am. Meteorol. Soc. 85, 771–773. [3] Bonacci, O. (1993). Hydrological identification of drought Hydrological Processes Volume 7, Issue 3, pages 249–262, July/ September 1993. [4] Belal A, Hassan R, El-Ramady, ElsayedS, Mohamed, Ahmed M, Saleh. 2012. Drought risk assessment using remote sensing and GIS techniques.Arab J Geosci DOI 10.1007/s12517-012-0707-2. [5] Bhalme, H.N. and Mooley, D.A. 1980. Large-scale drought / floods and monsoon circulation. Mon. Weather Rev. 108 (8):1197–1211. [6] Brown, J.F., Wardlow, B.D., Tadesse, T., Hayes, M.J., and Reed, B.C. 2008. The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation. GIS Science and Remote Sensing, 45 (1): 16–46. [7] Bryant, S., Arnell, N.W., and Law, F.M. 1992. The long-term context for the current hydrological drought. Institute of Water and Environmental Management (IWEM) Conference on the management of scarce water resources. 13–14 October 1992. [8] Cai, G., Du, M., and Liu, Y. 2011. Regional drought monitoring and analyzing using MODIS data—A case study in Yunnan Province. In Computer and Computing Technologies in Agriculture IV. Edited by D. Li, Yande Liu, and Y. Chen. Springer, Boston. pp. 243–251. [9] Clausen B, Pearson CP (1995). Regional frequency analysis of annual maximum streamflow drought. J. Hydrol. 173(1–4): 111-130. [10] Dai A (2010) Drought under global warming: A review. WIREs Clim Chang 2:45– 65.doi:10.1002/wcc.81. [11] Desai et al. (2008).Development of a simplified drought index and its comparison with standardised precipitation index. Journal of Hydrological Research and Development, Vol. 23, p. 109-123 (2008). [12] Droughtscore.com.2007 Sperling Drought Index Methodology. (accessed22 April 2011). [13] G.P. Zhang.2003. Time series forecasting using a hybrid ARIMA and neural network model Neurocomputing 50 (2003) 159-175. [14] Gommes, R.A., and Petrassi, F. 1994. Rainfall variability and drought in sub-Saharan Africa since 1960. Rome, Italy. 100 p. [15] Griffiths G 1990 Rainfall deficits: Distribution of monthly runs. Journal of Hydrology Volume 115, Issues 1–4, July 1990, Pages 219–229 [16] Heim, R. R. 2002. A Review of Twentieth-Century Drought Indices Used in the United States. Bulletin of the American Meteorological Society 83: 1149–1165. [17] Hisdal, H., Tallaksen, L.M., Clausen, B., Peters, E., Gustard, A. (2004). Hydrological Drought Characteristics. In: Tallaksen, L.M. & Lanen, H.A.J. van (2004) (Eds) Hydrological Drought – Processes and Estimation Methods for Streamflow and Groundwater Developments in Water Sciences 48, Elsevier Science BV, The Netherlands, 139-198. [18] J. Rhee, G.J. Carbone, and J. Im, Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data, Remote Sensing of Environment, vol. 114, no. 12, pp. 2875–2887, 2010. [19] Kjeldsen, T.R., Lundorf A. & Rosbjerg, D. (2000) Use of a two-component exponential distribution in partial duration modelling of hydrological droughts in Zimbabwean rivers.Hydrol.Sci.J.45(2), 285-298.

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[20] Kogan, F.N. 2000. “Contribution of Remote Sensing to Drought Early Warning. In Early Warning Systems for Drought Preparedness and Drought Management. Proceedings of the Expert Group Meeting, edited by D.A. Wilhite, M.V.K. Sivakumar and D.A. Wood, Lisbon. World Meteorological Organization, 86–100. Accessed March 12, 2013. http://www. wamis.org/agm/ pubs/agm2/agm02.pdf. [21] K. Yurekli, K. Kurunc, F. Ozturk, Application of linear stochastic models to monthly flow data of Kelkit stream, Ecological Modeling 183 (2005) 67-75. [22] Li X, Wang Y, TangS, ShenlS, 2012. NDVI-L S T Feature Space Based Drought Monitoring using MERSI Data in Hunan Province of China.IEEE conference publications. [23] McKee, T.B., Doesken, N.J., and Kleist, J. 1993. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology Anaheim, Calif. 17–22 January 1993. American Meteorological Society. [24] McVicar, T.R. and D.L.B. Jupp. 1998. The Current and Potential Operational Uses of Remote Sensing to Aid Decisions on Drought Exceptional Circumstances in Australia: A Review. Agriculture System 57: 399–468. [25] Mishra, A.K. and V.P. Singh. 2010. A Review of Drought Concepts. Journal of Hydrology 391: 202–216. [26] Mishra, A.K. and V.P. Singh. 2011. Review Papers Drought modeling – A review. Journal of Hydrology 403 (2011) 157–175. [27] Niemeyer S. New drought indices. In: López-Fran cos A. (ed.). Drought management: scientific and technological innovations. Zaragoza: CIHEAM, 2 008. pp. 267-274. [28] Niemeyer S. New drought indices. In: López-Fran cos A. (ed.). Drought management: scientific and technological innovations. Zaragoza: CIHEAM, 2 008. p. 2 67 -2 7 4 [29] Palmer, W.C. 1965. Meteorological drought. Weather Bureau Research Paper No. 45, US Department of Commerce, Washington, DC. 58 pp. [30] Palmer, W.C. 1968. Keeping track of crop moisture conditions, nationwide: The new crop moisture index. Weather wise, 21(4): 156–161. [31] Rhee, J., Im, J., and Carbone, G.J. 2010. Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sens. Environ. 114 (12): 2875–2887. doi: 10. 1016/j.rse.2010.07.005. [32] Shafer, B., and Dezman, L. (1982). Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. Proceedings of the Western Snow Conference, pp. 164–175. [33] Sivakumar, M. V. K., Motha, R. P., Wilhite, D. A., and Wood, D. A. 2011. Agricultural Drought Indices — Proceedings of an Expert meeting. 219 pp. [34] Stahl, K. & Demuth, S. (1999) Linking streamflow drought to the occurrence of atmospheric circulation patterns. Hydrological Sciences Journal, 44 (3): 467-482. [35] Svoboda, M.D., LeComte, D. and Hayes, M.J. 2002. The Drought Monitor. Bull. Am. Meteorol. Soc. 93 (8): 1181–1190. [36] Tadesse, T., and Wardlow, B. 2007. The Vegetation Outlook (VegOut): A new tool for providing outlooks of general vegetation conditions using data mining techniques. [37] Tate, E.L and Freeman,S.N (2000) Three modelling approaches for seasonal streamflow droughts in Southern Africa: The use of censored data. Hydrol .Sci.j 45 (1), 27-42. [38] Tsakiris, G. and Vangelis, H. 2005. Establishing a drought index incorporating evapotranspiration. European Water, 9 (10): 3–11. [39] Van-Rooy, M.P. 1965. A rainfall anomaly index (RAI) independent of time and space. Notos, 14: 43–48. [40] Vasiliades, L., Loukas, A., and Liberis, N. 2011. A water balance derived drought index for Pinios River Basin, Greece. Water Resources Management, 25(4): 1087–1101. [41] Wang, L., and J. J. Qu. 2009.Satellite Remote Sensing Applications for Surface Soil Moisture Monitoring: A Review. Frontiers of Earth Science in China 3: 237–247. [42] Weghorst, K. 1996. The reclamation drought index: guidelines and practical applications. cedb.asce.org, ASCE, Denver, Colo. [43] Wilhite, D.A., Glantz, M.H., 1985. Understanding the drought phenomenon: the role of definitions. Water Int. 10, 111–120. [44] WMO 2009. Lincoln declaration on drought indices. World Meteorological Organization (accessed 22 April 2011). [45] World Meteorological Organization (WMO) (1986) Report on drought and countries affected by drought during 1974–1985. WMO, Geneva, p. 118 [46] Yagci A, Liping Di, Meixia Deng, Genong Yu and Chunming Peng. Global Agricultural Drought Mapping: Results for the Year 2011. IGARSS 2012. [47] Zargar A., Sadiq R., Naser B. and KhanF.2011.A review of drought indices. NRC Research Press.Environ. Rev. 19: 333–349 (2011) doi: 10.1139/A11-013. [48] Zelenhasic E. and Salvai A. 1987 A method of streamflow drought analysis Water.Resour.Res.23 (1) 156-168. [49] Zhang, J., Y. Xu, F. Yao, P.Wang, W. Guo, L. Li, and L. Yang. 2010. “Advances in Estimation Methods of Vegetation Water Content Based on Optical Remote Sensing Techniques. Science China- Technological Sciences 53: 1159–1167 [50] Zhang N, Hong Y, Qin Q, and Liu L VSDI: a visible and shortwave infrared drought index for monitoring soil and vegetation moisture based on optical remote sensing. International Journal of Remote Sensing, 2013. Vol. 34, No. 13, 4585–4609. [51] Zhou L, Wu J, Zhang J, Leng S, Liu M, Zhang J, Zhao L, Zhang F, and ShiY The Integrated Surface Drought Index (ISDI) as an Indicator for Agricultural Drought Monitoring.Theory, Validation, and Application in Mid-Eastern China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6, No. 3, June 2013.

[372] Structural Design of Safe Building Skin in Seismic Area

Er. Dukhi Sah Chief Technical Advisor, Police Building Construction Cooperation Govt. of Bihar, Patna, Bihar, India

ABSTRACT Building skins, a non- structural member, play important role in architectural façade, building enclosure, optimizing outside environment and have useful impact on habitants in their living conditions and quality of life. As a green building tool, building skin system has to provide solutions to large domain of variations as regards to weather conditions/ climatic conditions of the particular country. Double skin façade with exterior walls have to cater varying ambient conditions integrating codal provisions regarding sun-shading, ventilations and thermal insulations etc. Third UN World Conference on Disaster Risk Reduction (WCDRR) Sendai, Japan, has resolved to substantially reduce global disaster mortality by 2030. In most parts of the world which fall in high seismic area, structural safety of the building skins/ non- structural elements require proper design consideration and vetting before adoption in constructions. Urbanization on major scale all over the world has created vast potentiality of advanced building skins as facade, claddings, infill walls etc. Considerable losses due to damage of non-structural elements and building contents including building skins have been experienced in past earthquakes. Advanced building skins, though prominently architectural feature, have to be adequately safe structurally. There is risk of injury, health hazards or death from falling panels, masonry or glass etc. Structural detailing of infill walls etc to be constructed within the frame of the structure and claddings attached to the primary structure require major design considerations. Double skin façade system is adopted increasingly as green building elements in many urban buildings which require thorough structural considerations. In India masonry infill walls are used as external walls as part of building envelope. Strength and stiffness of these walls are conservatively assumed. To avoid failure interaction of infill wall with frame, these walls are required to be designed considering lateral loads/ wind loads. Building skins poorly connected to frames/ structural members are more likely get damaged due to out–of-plane vibrations or having large weak plane panels. Extent of damage depends on strength of such panels. The paper will cover the design parameters/ considerations adopted for light/ medium/ heavy type claddings/ facades by some of the seismic prone countries. For many types of building skins, proper design criteria are still to be decided which pose serious threat to life safety. Challenges are vast in codifying the guide lines and parameters pertaining to different types of materials in use for building skins including/ claddings/ facades- single or double skin system. Standardized design regulations for suppliers and erectors will ensure safe and quality constructions. Presently no standard/ code is available specifically for designs and / or installation of façade system/ building skins in general and for prone areas as well. Keywords: Non-structural Element, Building Skin, Seismic Prone Area, Structural Design

[373] Estimation of Manning’s Roughness Coefficient at Baharwa Ghat of River Ganga, Patna

Shashi Ranjan1, Vivekanand Singh2, Manish Kumar Ranjan3 and Anshu Raj4 1Research Scholar, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 2Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India 3,4B.Tech Students, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India E-mail: [email protected], [email protected]

ABSTRACT Calculations of stream discharge and floodwater elevations require evaluation of the flow impeding characteristics of stream channels and their banks. Manning’s roughness coefficient (n) is commonly used to assign a quantitative value to represent the collective effect of these characteristics. The procedure for estimating Manning’s n values generally is subjective, and the accuracy is largely dependent on a hydrologist’s or engineer’s experience in estimating these values over a wide range of hydraulic conditions. Even experienced hydrologists sometimes have difficulty in assessing accurately all the factors that contribute to flow resistance. Thus the estimation of Manning’s roughness is very important for the computation of the discharge. Many empirical formulae have been presented for computing Manning’s coefficient n in natural streams and it is related to the bed material size. Most popular form of the empirical equation used for estimating Manning’s roughness coefficient is the Strickler formula, which is related to the bed materials. In this paper, the Manning’s roughness has been estimated using the empirical formula given by Strickler at Baharwa Ghat of River Ganga at Patna. For this purpose, five (05) samples from the bed of river Ganga have been collected across river Ganga at Baharwa Ghat. Grain size analysis have been conducted in the laboratory and percentage finer has been computed. Based on the mean grain size the Mannings roughness has been estimated for all the soil samples. Estimated roughness coefficient was

varying from 0.01 to 0.02. Further, Coefficient of uniformity (Cu) and Coefficient of curvature (Cc) were

also computed. The value of Cu is less than 4 and Cc is less than 1 that indicates soil is poorly graded soil. Keywords: Manning’s Roughness Coefficient, Strickler Formula, Baharwa Ghat, River Ganga

1. INTRODUCTION Hydraulic calculations to determine flow in open channels require an evaluation of all characteristics that affect the roughness of the main channel or stream. The Manning’s roughness coefficient, n, is used to describe the flow resistance or relative roughness of a channel and is a function of the bed material, depth of flow, cross-section geometry, channel variations, obstructions to flow, type and density of vegetation, and degree of channel meandering. Term n appears in the general Manning equation for open-channel flow. The Manning equation, along with energy and continuity equations, can be used for the indirect computations of stream flow and has applications in flood-engineering studies, bridge and highway design, or other hydraulic computations. Extensive guidelines for the selection of roughness characteristics are available (Chow, 1959; Arcement and Schneider, 1989; Jarrett, 1985; Coon, 1995). The selection of roughness coefficients for stream channels and the overbank areas has been a subjective art rather than a quantitative science. The ability to determine roughness coefficients for natural channels representing a wide range of conditions needs to be developed through experience. Experience can be obtained in several ways, namely (1) understanding the factors that affect the value of the roughness coefficient, and thus acquiring a basic knowledge of the problem, (2) consulting and using a table of typical roughness coefficients for channels, and (3) examining and becoming acquainted with the appearance of some typical channels whose roughness coefficients are known. The photographs and data presented in literatures cover

[374] Estimation of Manning’s Roughness Coefficient at Baharwa Ghat of River Ganga, Patna a wide range of conditions. Familiarity with channel geometry, appearance, and roughness coefficients of these channels will improve the ability to select roughness coefficients for other similar channels. Several other factors that contribute to energy losses during large floods are unsteady flow, flood-plain flow that crosses the main channel in a meander bend, transport and jamming of debris, extreme turbulence, bed forms in non-cohesive bed material, and shear stresses at the interface between flood plain and main channel (Trieste and Jarrett, 1987). The interaction of two or more of these factors could further affect channel-energy loss. Although these factors are identifiable, their individual contributions to the total roughness are difficult, if not impossible, to quantify. As a result, several methods for estimating n values have been developed. In response to a need for assessment of roughness coefficients that are representative of the Ganga river at Baharwa Ghat Patna, this study has been conducted. The main objective of this study is to estimate the Manning’s roughness coefficient, n using the empirical formula at Baharwa Ghat in River Ganga at Patna.

2. STUDY AREA Study area is the River Ganga at Baharwa ghat site at Patna. Locations of the soil sample have been shown in Figure 1. Baharwa ghat is approximately 500 m downstream of Gandhi ghat, which is situated on the right bank of river Ganga behind National Institute of Technology Patna. Soil samples have been collected from 5 different locations across the river at Baharwa ghat as shown in Figure 1.

Fig. 1: Location Map of Soil Sampling Sites Across River Ganga at Baharwa Ghat Patna

3. METHODOLOGY Five soil samples have been collected from the bed of river Ganga at Baharwa ghat. First sample was collected from outside of river water and second sample was taken from inside of the river water on right bank of River. Third sample was taken from the island and fourth was from the outside of water and fifth was from inside of water on left side of the main water channel of river Ganga. Grain size analyses of these samples have been conducted in the laboratory of NIT Patna. The curves for the percentage finer against the particle size have been drawn and different percentage finer (such as d10, d30, d50, d60, d90) have been determined from the curve. The empirical formulas used to estimate the Manning’s roughness coefficient are given below (Subramanya, 2015): [375] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Strickler formula:

Meyer et al.

where, d50 and d90 are in meters and represent the particle size of 50 percent and 90 percent of the bed materials are finer than d50 and d90, respectively.

Coefficient of Uniformity (Cu)

Coefficient of Curvature (Cc)

4. RESULTS AND DISCUSSION Five soil samples have been collected from different locations across the section of river Ganga at Baharwa ghat at Patna. Grain size analysis has been carried out in Geotechnical Laboratory of Civil Engineering Department, NIT Patna. Table 1 presents the percentage passing of all soil samples through different sieve number. It can be seen that the samples collected from inside water are coarser than the sample collected outside water. Particle size distribution showed that most of the soil samples were sands and small amount of silt that described soil was sandy loam type soil. Figures 2 to Figure 6 presents the plot of percent passing versus grain size of the bed materials. From these curves the values of d10, d30, d50, d60 and d90 have been computed, which have been used for the calculation of Coefficient of Uniformity (Cu) and Coefficient of Curvature (Cc) and Mannings roughness coefficient for all the soil samples.

Table 1: Details of Grain Size Distribution of All the Soil Samples Sieve Size % Passing of % Passing of % Passing of % Passing of % Passing of (mm) Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 4.75 100 100 100 100 100 2.36 99.65 98.85 98.85 98.68 100 1.18 88.35 95.8 87.1 92.2 99.6 0.600 79.15 94.6 80.85 85.6 98.3 0.425 72.55 94.05 79.45 80.76 94.1 0.300 69 92.95 77.9 77.23 83.96 0.150 53.32 59.7 66.9 58.1 52.3 0.075 23.1 11.45 9.7 11.13 17.53 Pan 1.68 1.4 0.3 0.06 1.71

[376] Estimation of Manning’s Roughness Coefficient at Baharwa Ghat of River Ganga, Patna

Fig. 2: Particle Size Distribution of Soil Sample 1 Fig. 3: Particle Size Distribution of Soil Sample 2 Table 2 presents the values of Coefficient of Uniformity (Cu) and Coefficient of Curvature (Cc) and Manning’s roughness coefficient for all the soil samples. All the values of Cu are less than 4 and Cc are less than 1, which reveals that soils are not well graded i.e. bed materials have an excess of certain particle and deficiency of others. Manning’s roughness coefficient varying from 0.0107 to 0.011 computed using Strickler formula and from 0.0099 to 0.0129 from Meyer et al. This also indicates that values computed using Strickler formula are lower than computed by Meyer et al. formula. As the Meyer et al. formula can be used for the coarse grain bed materials, which is reflected from these results also. These values of manning roughness coefficient matches well with the values given in the standard text book (Subramanya 2015) for the natural stream. Equivalent roughness may be computed based on these values at Baharwa ghat of river Ganga, may be used to compute the discharge.

Fig. 4: Particle Size Distribution of Soil Sample 3 Fig. 5: Particle Size Distribution of Soil Sample 4

[377] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 6: Particle Size Distribution of Soil Sample 5

Table 2: Computed Values of Coefficient of Uniformity, Coefficient of Curvature and Manning’s Roughness

Computed Manning’s Soil d Coefficient d (mm) d (mm) d (mm) d (mm) 90 Cu Cc Sample 10 30 50 60 (mm) Meyer et al. Strickler Method Method 1 0.075 0.088 0.148 0.198 1.340 2.64 0.046 0.0109 0.0128 2 0.078 0.098 0.140 0.160 0.290 2.05 0.054 0.0108 0.0099 3 0.078 0.020 0.131 0.149 1.410 1.91 0.043 0.0107 0.0129 4 0.073 0.020 0.158 0.182 1.080 2.49 0.036 0.0110 0.0123 5 0.073 0.020 0.160 0.182 0.370 2.49 0.036 0.0110 0.0103

5. CONCLUSION Manning’s roughness coefficients are estimated at Baharwa ghat of river Ganga at Patna. The empirical formulas i.e. Strickler and Meyer et al. have been used to compute the values based on the mean particles size of the bed materials. Five soil samples have been collected from the bed of river Ganga at Baharwa ghat across the section and grain size distribution have been carried out. Based on the particle size distribution the required percent passing size have been taken from the curve and finally Manning roughness coefficient have been calculated. The values of Manning’s coefficient varying from 0.0107 to 0.011, calculated using Strickler formula and from 0.0099 to 0.0129 calculated using Meyer et al. formula.

The values of Cu are less than 4 whereas the values of CC are less than 1, it reveals that bed materials are poorly graded.

[378] Estimation of Manning’s Roughness Coefficient at Baharwa Ghat of River Ganga, Patna REFRENCES [1] Arcement, G.J. and Schneider, V.R., 1989, Guide for selecting Manning’s roughness coefficients for natural channels and flood plains: U.S. Geological Survey Water-Supply Paper 2339, p. 38. [2] Chow, V.T. 1959. Open-channel hydraulics: New York, McGraw-Hill, p. 680. [3] Coon, W. F., 1995, Estimates of roughness coefficients for selected natural stream channels with vegetated banks in New York: U.S. Geological Survey Open-File Report 93-161, p. 127. [4] Jarrett, R.D., 1985, Determination of roughness coefficients for streams in Colorado: U.S. Geological Survey Water- Resources Investigations Report 85-4004, p. 54. [5] Subramanya, K, 2015, Flow in Open Channels, 4th Edition, McGraw Hill Edu. (India) Pvt. Ltd., New Delhi. [6] Trieste, D.J., and Jarrett, R.D., 1987, Roughness coefficients of large floods, in James, L.G., and English, M.J., eds., Irrigation and Drainage Division Specialty Conference, “Irrigation Systems for the 21st Century,” Portland, Ore., Proceedings: New York, American Society of Civil Engineers, p. 32-40.

[379] Comparative Study of Normal Clay Bricks, Fly Ash Bricks and Papercrete Bricks

Supriya Kumari1, Dr. Ajay Kumar2 and Dr. Ravish Kumar3 1Research Scholar, Architecture Department, National Institute of Technology Patna, Bihar, India 2,3Assistant Professor, Architecture Department, National Institute of Technology Patna, Bihar, India E-mail: [email protected]

ABSTRACT Presently there are various imaginative low-cost construction methods and alternate building materials are being utilized since long back fulfils useful just as particular prerequisites of conventional materials/ procedures and provide an avenue for the drop-down the development cost and environmentally friendly. The main aim of this paper to make a comparative study of the main three bricks types namely normal clay brick, fly ash brick and Papercrete brick and their properties like absorption, crushing strength, hardness etc. Clay brick being used from the last many decades in building construction. Clay brick is very important and common construction material which is used in all masonry work. A large land area is used for acquired clay for brick making. Normal clay brick is a clay product, made by the help of clay mould (it can be table moulded or ground moulded) and baked in kiln or clamp. Clay is the main part of productive land and to solve this problem, Fly Ash brick has come as a non-conventional brick. Fly Ash brick helps in converting industrial waste material into quality building material as well as it is strong, effective and economical than the clay brick. Papercrete is a kind of fibrous cement or stringy bond, made by waste item like an old newspaper, cardboards etc. as pulp in water, Portland cement and sandy soil. Papercrete has the property of good fire-resistant, sound retention and thermal insulation and numerous advantages in the construction industry such as cost-effective, light and more flexible material and aesthetic. Keyword: Normal Clay Bricks, Fly Ash Bricks, Papercrete Bricks

1. INTRODUCTION Since the last few years, there was an increase in demand for different building material which had some new techniques. It has been informed that marking bricks with conventional material is becoming costlier day by day. This is chiefly for marking conventional brick of higher compressive strengths. The conventional brick is susceptible to efflorescence and due to which the weakness of conventional brick masonry due to great adsorption of water is well known. This has turned into a noteworthy challenge to architects to create and utilized alternate materials. Industrial waste has been converted to useful construction and building materials. This analysis examines the potential utilization of waste paper for creating a minimal cost and lightweight composite block as a building material. More than 450 million tons of paper is generated per annum worldwide and it is anticipated that the interest for the paper will arrive at 500 million per annum before the end of 2020 [1]. Papercrete material has been found in 1928 but rediscovered recently due to the enhancement of recycled material. In the country like India no. of homeless people increasing day by day. One of the causes of homeless is the high cost of building material. Green materials are presently the favoured material for development since they are proficient of lighter weight and affordable. Papercrete brick is one of the most important building material which can be manufactured by using waste paper and it is inexpensive too.

[380] Comparative Study of Normal Clay Bricks,Fly Ash Bricks and Papercrete Bricks Papercrete is a composite material involving Portland cement, squander paper, water and additionally sand. It resembles supplanting coursing-grained division or potentially sand of Portland cement with squander paper. Papercrete has been accounted for: to be shoddy alternative building material; to have great sound retention and thermal insulation; to be a lightweight and fireproof material [2].

2. AIM & OBJECTIVES OF THE RESEARCH The main aim of this paper to make a comparative study of the main three types of bricks with their properties like absorption, compressive strength, structural strength.

3. OBJECTIVE OF THE RESEARCH ●● To compare conventional brick i.e. clay brick and non-conventional brick i.e. fly ash & papercrete brick. ●● To determine the suitable brick according to its compressive strength. ●● To determine its need according to location and cost optimization of different types of brick. ●● To reduce the expense in comparison to conventional building bricks by utilizing inventive and alternative non-conventional bricks.

4. METHODOLOGY

BACKGROUND STUDY OF BRICK TYPES

SELECTION OF BRICK SELECTION OF THE LITERATURE OF TYPES RESEARCH AREA

SECONDARY DATA COLLECTION Journals, Images

DATA ANALYSIS (Comparison of literature)

RESULT AND DISCUSSION

CONCLUSION

FUTURE SCOPE

[381] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 5. MATERIAL AND PROPERTIES

5.1 Conventional Brick Building brick is normally made of a blend of clay and sand, which are blended and shape in different ways, after which they are dried and burnt. Clay for brick causing must to create appropriate plasticity and be equipped for drying rapidly without exorbitant shrinkage, warping or cracking and of being burnt to desired texture and strength. Conventional clay bricks are the standard unit of traditional building construction. Bricks have been utilized since earlier times for walls and columns of making residential and non-residential buildings. The brick is produced using soil and subsequently, the property of bricks relies upon the properties of soil.

5.2 Structure of Clay Brick Raw materials required for manufacturing of clay, silt and sand. Following below are the constituents of good brick: ●● ALUMINA: This component helps to mould the clay which imparts plasticity in it. It contains 20–30% of alumina. ●● SILICA: The presence of silica prevents cracking, shrinkage and twisting of crude bricks. 50–60% of silica should be contained by Good brick. ●● LIME: Shrinkage of raw bricks is prevented by Lime. Brick should contain no more than 5% of lime because brick lost its shape and get melted by an excess of lime. ●● OXIDE OF IRON: It imparts a red colour to the bricks. It should contain 5–6% of iron oxide. ●● MAGNESIA: A small quantity of this constituent imparts yellow tint to brick and it decreases shrinkages.

5.3 Properties of Clay Brick ●● Colour ●● Shape & Size ●● Texture ●● Soundness ●● Hardness ●● Strength ●● Water Absorption ●● Efflorescence ●● Thermal Conductivity ●● Sound Insulation ●● Fire Resistance

5.4 Manufacture of Clay Brick The four distinct stages of manufacturing the mould clay bricks are: 1. Preparation of brick from the earth/soil 2. Moulding clay in rectangular blocks of uniform size

[382] Comparative Study of Normal Clay Bricks,Fly Ash Bricks and Papercrete Bricks 3. Drying in sun and air 4. Burning them in brick clamps and kilns 5. Storing finished products.

Fig. 1: Schematic Diagram of Clay Brick Making Machine [10]

6. FLY ASH BRICKS Our bricks are fabricated utilizing Fly ash (a waste materials from the thermal power plant), stone residue, and cement (OPC Grade). Their assembling takes out Fly Ash from the earth as a poison and simultaneously gives a green structure material to the development industry. There is an enormous market for these bricks and its various uses in building construction, development of asphalts, dam, tanks, underwater works, waterways lining, irrigation work, etc. and the main thing required is mindfulness about its advantages.

6.1 Composition of Fly Ash Brick They recommended the accompanying materials can be utilized for the composition of fly ash brick: Fly Ash: Fly ash is finely isolated buildup coming about because of the burning of powdered coal, shipped by the pipe gases and gathered by electrostatic precipitators. Its legitimate transfer has been a reason for perturbing since long, which generally prompts contamination of air, soil and water. It likewise improves usefulness and lessens inward temperature. Red Soil: Red soil commonly got from the crystalline stone. They are normally poor developing soils, low in supplements and people and hard to develop in light of its low water-holding limit. Unprocessed materials required for assembling of Fly ash bricks are Fly Ash, lime, gypsum and sand (discretionary).

[383] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

6.2 Properties of Fly Ash Brick ●● Strength ●● Reduced Efflorescence ●● Reduced Shrinkage ●● Workability ●● Improved Finishing ●● Magnificent Thermal Insulation ●● Good in Sound Insulation ●● Fire Resistance

6.3 Manufacture of Clay Brick Required crude material like fly ash, gypsum, alum and stone ponding residue must be blended according to the proportion. The blended item can be put into an automatic locking mechanism. This to be kept in moulds for assembling of automatic locking fly ash bricks. After the final processing, the block has can be sold. The entire assembling procedure is shown underneath the figure.

Fig. 2: Schematic Diagram of Fly Ash Brick Making Machine [11]

6.4 Advantages of Fly Ash Bricks [3] ●● High Compressive Strength: Fly Ash Bricks have a thick arrangement and high compressive quality which gives them higher load-bearing capacity when contrasted with clay bricks. Likewise, they have nearly nil wastage during transportation. ●● Light Weight: These are 12% lighter when contrasted to clay bricks. In this way, it is appropriate for multi-storey building and lesser weight implies a decrease in structure’s dead load, and in this manner less weight on the building, safety assured. ●● Uniform Size & Shape: Fly Ash Bricks are uniform in shape and size (230 X 115 X 75mm) and have a far superior completion when contrasted with clay bricks.

[384] Comparative Study of Normal Clay Bricks,Fly Ash Bricks and Papercrete Bricks ●● Thermal Insulation: Fly Ash Bricks have preferable thermal protection than clay bricks. They don’t ingest heat, rather they reflect heat. Consequently, they keep the inner part of the structure/ houses cooler even in summer henceforth they are increasingly appropriate for the nearby condition and can save money on the power bill. ●● Optimum Water Absorption: They are less permeable, retains less water, while burnt clay bricks consumed assimilate more water during construction. Hence, they help in water-sparing during construction and decrease odds of moistness on dividers/walls during the rainy season. Fly Ash Bricks have ideal water retention of around 12- 13% required for plastering, unlike cement bricks that have water assimilation of around 5-6%, in this way making them difficult for plastering. ●● Ease of Work: Inferable from its ideal quality, it tends to be penetrated, sawed, nailed and chiseled in all respects helpfully with both manual and power-driven instruments without chipping or cracking, not at all like cement bricks which cannot be bored or chiseled utilizing manual apparatuses and gets cracked due to its bizarrely high compressive strength. ●● Noise Insulation: For noise insulation fly ash brick are twice preferable than clay bricks. ●● Energy Efficient: These are environment-friendly as its having more green products. Their procedure of assembling is less vitality escalated when contrasted with clay bricks. They help in keeping nature spotless as they utilize fly ash (over half of its weight), therefore gives the most valuable arrangement.

7. PAPERCRETE Papercrete is a sort of fibrous cement, made by old papers and waste papers which mash into the water and including Portland cement with it. The thick blend would then be able to be filled into moulds and cast like brick, making squares, boards and incalculable different shapes. After restored and dried, papercrete is sloid, lightweight, protection and has numerous properties which make it a perfect construction material.

7.1 Materials Used Paper: In this research paper, the paper is the main component. Various sorts of papers similar type of newspapers, magazines, and so on. Paper is wood cellulose, which is considered as a stringy material. Cement: Cement utilized in this research was 53 grade Ordinary Portland cement (OPC) conforming to IS: 8112-1989 cement used. Fine Aggregates: Fine Aggregates used was river sand and fabricated sand (M-Sand) passing 4.75mm IS sieve as per the specification in IS: 383-1970 were used [4].

Fig. 3: Soaking of Newspaper Fig. 4: Paper Pulp Fig. 5: Mixing of Ingredients

[385] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 6: Moulding of Brick Fig. 7: Remoulding of Brick Fig. 8: Dry Papercrete Brick

7.2 Properties of Papercrete [5] ●● Compressive Strength: Compressive quality tests on 15 cm x 15 cm x 15 cm papercrete 3D shapes uncovered a normal compressive strength of 0.57 N/mm2 after 3 days of cube preparation. Other research likewise proposes comparative outcomes. [1, 5]. For more strength, a higher grade of cement can be utilized. ●● Weight and Density: Density of the material expanded with increment in the percentage of cement in the blend and decreased with increment in the quantity of the paper in the mixture. The normal load of 8 cubes cast was seen to be 3.624 kg, in this manner block volume was about 1.07 gm /cc. This is thusly lightweight in contrast with standard cement or block brickwork units. ●● Shrinkage: 8-9% shrinkage was estimated in each block. ●● Water Absorption: In all case, about 30% was the water absorption of the blocks. ●● Drying Time: 40 hours, at any rate, are required for drying of papercrete before it can be moulded. After this, it ought to be sundried for 4 days before use for better quality and strength. Or on the other hand, it tends to be set in a clamp/oven at about 70 °C for 40 hours after casting. Putting it at a higher temperature than this can bring about the isolation of material. ●● Tests for different properties, for example, 7 days and 28 days compressive strength, thermal resistance, sound insulation, behaviour under fire so forth are under advancement. ●● Presence of Soluble Salts: The soluble salts, if present in bricks will cause efflorescence on the outside of bricks surface. For 24 hours the brick was soaked in water and afterwards were taken out and made it dry in shades. Grey or white stores were not found on the outside of the surface of the brick which concludes that the bricks are free from soluble salts.

7.3 Advantages and Disadvantages of Papercrete Papercrete can be delivered by using solar energy. The main power need is to blend. Papercrete has striking protecting characteristics and it is far lighter in weight, unlike concrete which is moderately substantial. It tends to be effectively moulded when restored and dried. The most significant advantages of papercrete are the decrease in cement in the blend. Carbon footprint during generation, the complete expenses and weight are diminished, bringing about an eco-accommodating and lightweight material. Paper fibres bring phenomenal insulating properties to heat and sound. Papercrete boosts the reusing of waste paper, particularly in communities with no reusing services. Papercrete is a practical choice for low-cost housing and shelters for short-term and workplaces. The high demand for building material leads to crisis and the need for finding an alternative source for recycling industrial waste. While making sustainable design wastepaper helps as low- cost and ecofriendly. India’s context just a small amount of paper is reused every year. This implies the rest is as yet discarded off, for the most part winding up in landfills for moderate degradation.

[386] Comparative Study of Normal Clay Bricks,Fly Ash Bricks and Papercrete Bricks The material has certain confinements in its application. Absence of official and literature data or rules on its preparation, auxiliary conduct or long haul practicality is one of the limitations for commercial use of the material. Papercrete is a fragile material. It grows and contracts regularly prompting to cracks, swelling and clasping and it has very low rigidity. It is hard to practice quality control of the blend cluster and acquire a smooth surface.

8. LIMITATION This paper is limited to the only theoretical background.

9. RESULT AND DISCUSSION OF CLAY BRICK AND FLY ASH BRICK

Table 1: Structural Strength Test Result of Fly Ash Brick [8] Structural 10 Brick Weight Load Average Structural Strenght 8 Specimen (Kg) (KN) Strength (N/mm2) (N/mm2) 6 F10 2.62 4 2.45 265 4.15 4.15 2 2.52 0 F20 2.92 21 days N/mmsq F10 F20 F30 F40 F50 2.59 495 7.5 7.5 Structuralstrength for 2.65 Mix Proportion F30 2.51 Fig. 9: Structural Strength Test [8] 2.53 598 9.07 9.07 2.67 F40 2.39 2.65 616 9.33 9.33 2.89 F50 2.96 2.92 372 8.46 8.46

Table 2: Compressive Strength Test Result of Fly Ash Brick [8] Compressive Average 10 Brick Weight Load Strenght Compressive Specimen (Kg) (KN) 8 (N/mm2) Strength (N/mm2) 6 F10 2.64 54.5 2.48 4 2.45 39.0 1.77 2.15 2 2.53 45.2 2.05

days N/mmsq 0 F20 2.62 82.2 2.98 strength for 21 COMPRESSIVE COMPRESSIVE F10 F20 F30 F40 F50 2.45 84.4 3.17 3.35 2.52 87.5 3.24 Mix Proportion F30 2.92 167.9 6.27 Fig. 10: Compressive Strength Test [8] 2.59 162.4 6.54 6.30 2.65 165.6 6.91 F40 2.79 196.1 8.91 2.83 207.4 9.43 9.17 2.95 210.9 9.19 F50 2.99 181.9 8.27 2.92 187.8 8.54 8.37

[387] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Table 3: Density Test Result of Fly Ash Brick [8] Volume 1800 Brick Weight Density Average Density of Bricks Specimen (Kg) (Kg/m3 (Kg/m3) 1700 (m3) 1600 F10 2.487 1.65 1507.27 1500 2.636 1.65 1597.57 1534.94 1400 2.495 1.65 1512.12 1300 F20 2.506 1.65 1518.79 Density kg/m3 F10 F20 F30 F40 F50 2.488 1.65 1507.88 1583.94 2.370 1.65 1436.36 Mix Proportion F30 2.326 1.65 1409.69 Fig. 11: Density Test [8] 2.790 1.65 1690.90 1644.85 2.902 1.65 1758.78 F40 2.810 1.65 1703.03 2.953 1.65 1789.69 1712.5 2.775 1.65 1681.82 F50 2.810 1.65 1703.03 2.953 1.65 1789.69 1703.02

Table 4: Compressive Strength for Both [6] Set-A Parameter Compressive Stregth psi (N/mmsq) Sample No. 1 2 3 4 Normal Clay Bricks 593.20(4.09) 522.13(3.6) 593.20(4.09) 1203.81(8.3) Fly Ash Brick 587.40(40.5) 826.71(5.7) 1556.25(1.073) 641.06(4.42) Set-B Parameter Compressive Stregth psi (N/mmsq) Sample No. 1 2 3 4 Normal Clay Bricks 652.66(4.5) 548.24(3.78) 651.2(4.49) 798(5.5) Fly Ash Brick 1130(7.71) 1150(7.93) 1102.2(7.6) 1160(8)

10. RESULT AND DISCUSSION OF PAPERCRETE BRICK

Table 5: Physical Characteristic of Papercrete Brick [7] Cement: Quarry Water Absorption Compressive Sl. No. Mix Designation Weight (Kg) Dust: Sand: Paper (%) Strength (N/mm2) 1 A1 1:3:4:6 39.54 2.2 1.86 2 A2 1:3:3:6 41.94 2.085 1.66 3 A3 1:3:2.5:6 48.11 1.99 1.37 4 B1 1:2:3:4 34.46 2.355 2.43 5 B2 1:2:4:4 31.81 2.45 2.51 6 B3 1:2:2.5:4 37.47 2.26 2.35 7 C1 1:1.5:2.5:2 23.26 2.80 2.91 8 C2 1:1.5:4:2 18.95 3.07 3.24 9 C3 1:1.5:3:2 33.3 2.52 3.03

[388] Comparative Study of Normal Clay Bricks,Fly Ash Bricks and Papercrete Bricks

Table 6: Water Absorption of Papercrete Brick [9] Sl. No. Type of Papercrete Water Bricks Absorption (%) 1 Water-cured 20.25 Table 7: Compressive Strength of Papercrete Brick [9] Type of Compressive Strength Papercrete Bricks 7 days 14 days 21 days Water-cured 1.025 1.10 1.40 Fig.12: Fire Resistance Test [9]

●● Fly ash utilized as squandered product and due to reducing solid waste disposal, the environment is directly protected. ●● Compressive Strength: Fly ash brick is 9 N/mm2 and clay brick is 5.5 N/mm2 ●● Save Land & Decrease Pollution: Fly ash used as crude material supplanting of clay to make fired bricks. ●● Fly ash modify the hydric properties of the bricks by lighter them. ●● All fly ash bricks have a lower density. ●● Fly ash bricks show less harm than conventional bricks when in contact with salt crystallization cycles. ●● Normal clay bricks have varying colour as per soil whereas Fly Ash bricks have a cement-like uniform pleasing colour. ●● Small scale preparation of papercrete bricks, its design and construction skills and also had a focus on the assessment of the properties of these building blocks. ●● It’s a sustainable building material. ●● Both clay brick, as well as fly ash brick, are suitable for load-bearing walls whereas, and for non- load bearing walls, papercrete bricks were suitable. ●● Papercrete can be moulded easily into any shape. ●● All of the brick types have good fire resistance. ●● The weight of papercrete brick is almost half of the weight of conventional clay bricks which reduces the dead load of the building.

Table 8: Compressive Strength of All Brick Types Comparative Analysis of Compressive Strength (N/mmsq) Sl. No. Normal Cray Bricks Fly Ash Bricks Papercrete 1 4.09 4.05 1.86 2 3.6 5.7 1.66 3 8.3 10.73 1.37 4 4.5 7.71 2.43 5 3.78 7.93 2.51 6 4.49 7.6 2.35 7 5.5 8 2.91 8 6.12 7.62 3.24 9 4.31 7.8 3.03

[389] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 11. CONCLUSION ●● After comparing all the 3 types of bricks with different mix designation we come to in conclusion of: o Fly Ash bricks having higher compressive strength. o Papercrete having lowest compressive strength therefore, it cannot be used as a load-bearing wall. o Papercrete is appropriate for low-cost housing and short-term shelters like slum development area, night shelter homes and workspaces and can help diminish carbon footprint. ●● This has been proved that the basic properties of Fly ash if used consciously and precisely it can be turned out to be a successful material. ●● Normal clay bricks are lightly attached whereas there is a thick piece on the composition of Fly Ash Bricks. ●● Plastering is required if there should be an occurrence of typical clay bricks though no plastering is required if there should arise an occurrence of Fly Ash Bricks. ●● Clay bricks are heavier than Fly Ash bricks ●● Fly Ash bricks are more water retention than that of clay bricks. ●● A Papercrete brick comprises of reused material in this manner, the expense is low contrasting to traditional bricks. ●● Papercrete bricks are lightweight and flexible thus these are the possibly perfect material for earthquake-prone areas. ●● Papercrete bricks are not good for external walls and areas of waterlogging. ●● Papercrete can be utilized as internal partition walls. ●● Modification of blend extends to accomplish ideal properties. ●● By using coconut fibres or fly ash compressive strength of papercrete can be improved. ●● Colour and surface texture can be used for better design and plan adaptability. ●● For waterproofing Silicon, concrete sealer or epoxy compound can be added of papercrete. ●● Replacing Cement by Fly ash in concrete mix will minimize environmental impact. ●● Papercrete reduces the environmental impacts caused by the burning and dumping of waste papers in the surroundings.

12. WAY FORWARD ●● Further study of papercrete bricks can be about gaining more compressive strength. ●● Another area of study can be about minimizing the water absorption in papercrete bricks.

Fig. 13: Arch Made by Papercrete [5]

[390] Comparative Study of Normal Clay Bricks,Fly Ash Bricks and Papercrete Bricks REFERENCES [1] P. Asha and P.R.P.P.P. Sarvankar Dipti, “Effect of paper waste on concrete properties: Sustainability approch,” IJESRT, 2017. [2] B. Nepal and V. Aggarwal, “Papercrete: A study on green structural material,” 2014. [3] G. CORP. [4] Y. Shermale and M. B. Varma, “Papercrete: An Efficient Use of Waste Paper,” STM, 2015. [5] J. Sheth, “Paper Crete: A Sustainable Building Material,” 2015. [6] P. Gadling and D.M. Varma, “Comparative Study on Fly Ash Bricks and Normal Clay Bricks,” IJSRD - International Journal for Scientific Research & Development, p. 673, 2016. [7] H.U. Momin and F.Y. Sayyad, “Highly compressed flyash based papercrete brick,” International Research Journal of Engineering and Technology, Vol. 04, no. 12, 2017. [8] K.K, M.N.M and D.D.G, “Performance of Fly Ash Brick Using Waste Materials,” IRJET, 2018. [9] M.M. Delcasse, R.V, A.C, P.M.K and Gangadhar, “Papercrete Bricks - An Alternative Sustainable Building Material,” IJERA, 2017. [10] “http://www.gobrick.com/advocate-for-brick/environmental,” [Online]. [11] “https://srikrishnaplasto.com/fly-ash-bricks/fly-ash-bricks-making-machines.html,” [Online].

[391] Rock Support Interaction Analysis and Design of Support

Upendra K. Singh Professor, Department of Mining Engineering, IIT(ISM), Dhanbad–826004

ABSTRACT The criterion that the stresses must always be less than the strength may therefore be sufficient to ensure the stability of a structure, but it is certainly not necessary. Observation of underground excavations surrounded by failed rock often shows that this rock, though failed, is still subject to stress. The analysis shows that a properly supported annulus of completely failed rock provides greatly enhanced support to the partially failed rock. The rational design of support and reinforcement systems must take into account the interaction between the support or reinforcing elements and the rock mass. Control of rock displacements is the major role of support and reinforcement systems. Enough displacement must be allowed to enable the rock mass strength to be mobilised sufficiently to restrict required support loads to practicable levels. However, excessive displacement, which would lead to a loosening of the rock mass and a reduction in its load- carrying capacity, must not be permitted to occur. The stiffness and the time of installation of the support element have an important influence on this displacement control. This paper describes basic concept of support for underground excavation and tunnels. It supplements the concept with a case study of design of lining of a vertical shaft in a mine. Principals of tunnel stabilization and lining are given, in this paper, for practicing engineers.

1. CRITERIA FOR THE DESIGN AND SUPPORT OF UNDERGROUND EXCAVATIONS In mechanical or civil engineering practice it is customary to ensure the stability of a structure by designing it so that the stresses in each element of the structure are always less than the strength of that element, defined in some appropriate way. This situation is achieved by a suitable choice of the material, section, and disposition of the elements of the structure. Despite the highly developed state of design in many fields of engineering, success depends as much on experience and empirical results as it does on any fundamental understanding of the behaviour of the material of the structure. Thus, the strength that is used may be the yield point, the ultimate strength, or the fatigue strength, depending upon the nature of the load to which the structure is subjected. Also, ‘safety factors’ are used to allow for uncertainties concerning the applicability of the analysis which is used and to allow for the variability in the properties of the materials which are used. The criterion that the stress should always be less than the strength would certainly appear to be adequate to ensure the stability of a structure and to be applicable to those structures in the form of underground excavations. However, the options which the designer of an excavation has available to him are far fewer than those available to his mechanical or civil engineering counterpart. In the first place, other than by moving the site of the excavation, there is no choice of an alternative material, though, to a limited extent, it may be possible to reinforce the rock surrounding the excavation, there is not choice of an alternative material, though, to a limited extent, it may be possible to reinforce the rock surrounding. Second, the rock around an excavation usually extends from the boundary of the excavation to the surface of the earth, so that the only options available in respect of the section and disposition of the neighboring excavations. These options are often circumscribed by other considerations, especially in mining, where the major excavation results from the extraction of the ore body. Situations, such as an isolated tunnel in hard rock, exist where it is possible to satisfy the usual design criterion despite these limitations. However, in many

[392] limited extent, it may be possible to reinforce the rock surrounding. Second, the rock around an excavation usually extends from the boundary of the excavation to the surface of the earth, so that the only options available in respect of the section and disposition of the neighboring excavations.Rock These Support options Interaction are often Analysis circumscribed and Design by of Supportother considerations, especially in mining, where the major excavation results from the extraction of the ore body. Situations, such as an excavations, especiallyisolated those tunnelresulting in hard from rock, mining, exist where it is not it is possible possible to satisfykeep the the stressesusual design everywhere criterion despite in the rock less than its strength.these Neitherlimitations. does However, experience in many indicate excavations, that especiallythis is necessary those resulting to ensure from mining,the stability it is not of the excavation. The rockpossible fails toin partskeep thesurrounding stresses everywhere many underground in the rock excavations,less than its butstrength. only occasionallyNeither does does this fact impair theexperience stability indicate or safety that of this the is excavation.necessary to ensureThe criterion the stability that of the the stressesexcavation. must The always rock fails be less than the strength mayin parts therefore surrounding be sufficientmany underground to ensure excavations, the stability but ofonly a structure,occasionally but does it is this certainly fact impair not necessary. In fact, it is theoften stability unacceptable, or safety of as the it excavation.would preclude The criterion mining thatin many the stres situationsses must and always excavation be less than the strength may therefore be sufficient to ensure the stability of a structure, but it is of tunnels and powerhousescertainly in not weak necessary and .highly In fact, stressed it is often ground unacceptable, where as it itis would practiced preclude with mining comparative in many safety. One is thereforesituations forced and to excavationexamine ofthe tunnels conditions and powerhouses which are in weaknecessary and highly for structuralstressed ground stability where if rock mechanics is to beit isapplied practiced usefully with comparative to the design safety. of One many is therefore underground forced toexcavations. examine the conditionsObservation which of underground excavationsare necessary surrounded for structural by failed stability rock often if rock shows mechanics that this is to rock, be applied though usefully failed, to is the still design subject of to stress. Turning to themany ideas underground developed excavations. in connection Observation with the of undergroundcomplete stress-strain excavations curvesurrounded for rock, by failed and the stiffness of testing machines,rock often shows they suggestthat this that,rock, while though the failed, stresses is still in thesubject failed to rockstress. must Turning have to exceeded the ideas developed in connection with the complete stress-strain curve for rock, and the stiffness of its strength, the stressestesting applied machines, to it arethey in suggest stable that, equilibrium while the stresseswith its in resistance the failed rockto them. must haveIt is exceededshown that its failure does not occur strength,when sufficient the stresses energy applied is to available it are in stable but equilibriumthe stresses with are its too resistance small, andto them. it now It is shseemsown that unstable failure cannotthat failure occur does even not occurwhen when the stressessufficient are energy adequate is available if insufficient but the stresses energy are istoo available. small, and it now seems that unstable failure cannot occur even when the stresses are adequate if insufficient energy is available. 2. FUNCTION OF SURFACE SUPPORT ON EXCAVATION (JAEGER AND COOK, 1979) 2. Function of surface support on excavation (Jaeger and Cook, 1979)

Fig. 1a:Fig. Fractured1a Fractured Rock rock Annulus annulus underunder hydrostatic Hydrostatic pressure Pressure supported Supported by support by reaction Pi

Support Reaction Pi

σ/P 2.0 Fractured zone Elastic zone 2

1.5 σθ/P 1.0

σr/P 0.5

0 1 2 3 r/a

Fig. 1b: Plot of Radial and Tangential Stress Build up in the Fractured and Fig.Elastic 1b. Plot Zone of radial as and Result tangential of stressApplication build up in ofthe Supportfractured and Reaction elastic zone Pi as =result 0.05P of application of support reaction Pi = 0.05P [393] Strength of unfractured rock is given by

1 Co  q3 (1) and the strength of fractured rock is assumed purely frictional i.e.

1  q f  3 (2)

2   2 1 / 2 1 sin f q f   f  1   f   1  sin  f

The solution for the radial and tangential stresses σr and σθ which satisfy the boundary condition is given by q 1  r  f   P  r i  a  (3)

q 1  r  f   q f pi   for a < r < re i.e. within the fractured annulus (4)  a 

e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) Strength of unfractured rock is given by (1) σ1 = Co + qσ 3 and the strength of fractured rock is assumed purely frictional i.e.

σ1 = q f σ 3 (2)

2 + φ 2 1/ 2 1 sin f q f = [(µ f +1) + µ f ] = 1− sinφ f

The solution for the radial and tangential stresses σr and σθ which satisfy the boundary condition is given by

(q −1)  r  f σ = P   (3) r i  a 

q f −1  r  for a < r < r i.e. within the fractured annulus (4) σθ = q p   e f i  a 

re is given by 1/(q −1)  −  f  2 p co  (5) re = a   (1+ q) pi 

o Numerical example: substituting φ = φf = 35 , Pi = 0.05P, Co = 0.5P in Eq. 5 give re = 1.99a. Figure 1b shows variation of radial and tangential stress build up in the fractured and elastic zone as result of application of support reaction Pi = 0.05. The analysis shows that a properly supported annulus of completely failed rock provides greatly enhanced support at re to the partially failed rock, which is equivalent to diminishing the field stresses by σr and enhancing the strength of the rock in accordance with the appropriate failure criterion (Eq. 1). If the support stress remains constant with radial compression, the stability of the tunnel is enhanced only as a result of these two factors. Support which generates an increasing stress with compression also enhances the stability of the tunnel by ‘softening’ the combined behaviour of the partially and completely failed annuli. The behaviour of the rock around a tunnel and its support can be summarized as follows: 1. Failure of the rock around a tunnel can occur without instability and violence and without complete loss of cohesion if the field stress is sufficient to start failure. 2. As the field stress increases, instability of the failed rock or complete loss of cohesion occurs, depending upon the properties of the rock. 3. If the fractured rock resulting from an unstable failure is retained by radial support stresses it can be used to enhance the effect of these stresses sufficiently to ensure that the partially failed annulus is kept to a stable thickness. 4. If the cohesion of the inner part of the annulus is completely destroyed by stable failure, radial support of this can be used both to retain the cohesion less material in place and to prevent further growth of the failed annuli.

[394] Rock Support Interaction Analysis and Design of Support Support is generally provided by linings, arches, or rock bolts. Provided that the rock bolts are sufficiently long to be anchored in the solid elastic rock and to disperse their loads, the support generated by all these techniques can be equated to σs. If shorter rock bolts are used which are anchored in the failed rock, as is often the case, some modification to Eq. 3 becomes necessary.

3. ROCK SUPPORT INTERACTION ANALYSIS Consider a tunnel of radius a to be excavated in hydrostatic stress field P. Before the excavation, the stress tractions at the boundary of the tunnel are equal and opposite to the field stress P. Let the stress traction acting from inside the tunnel be Pi, as shown in Fig. 2, is equal to the field stress P before the excavation.

We call Pi support pressure. The excavation of the tunnel can be simulated by equating Pi = 0. Now, we gradually decrease the support pressure Pi and record closure of the tunnel boundary. This process can be easily simulated by a FE software using non-linear plasticity model. Plot of tunnel closure vis-à-vis support pressure is recorded in Fig. 3 for four different strengths of rock. The rock strength and support pressures are normalized with in-situ hydrostatic stresses to generalize the results. Closure of the tunnel is also expressed as percentage of its diameter. normalized with in-situ hydrostatic stresses to generalize the results. Closure of the tunnel is also For rock of strengthexpressed in-situ as percentage stress ratioof its diameter.1, the boundary stress of the circular tunnel is twice the strength of rock. Therefore, failureFor rock of of rock strength occurs in-situ at stress the ratio periphery 1, the boundary of the stress tunnel. of the Atcircular 1% tunnelsupport is pressure, 0.76 % closure of the tunneltwice the occurs. strength Withof rock. further Therefore, decrease failure of inrock strength occurs at ofthe the periphery rock, of closure the tunnel. of At the 1% tunnel increases (Fig. 3). Field observationssupport pressure, have 0.76 %shown closure ofthat the iftunnel we occurs.permit With uncontrolled further decrease deformationin strength of the of tunnel in excess rock, closure of the tunnel increases (Fig. 3). Field observations have shown that if we permit of 1% closure, theuncontrolled rock in deformation failed annulus of tunnel losses in excess it integrityof 1% closure, and the unable rock in failedto provide annulus lossessupport it as discussed in section 2. Thus,integrity it is recommended and unable to provide that supporttunnel as closure discussed should in section not 2. beThus, permitted it is recommended beyond that 4 percent of tunnel radius, to be ontunnel safer closure side (Singh,should not 2006). be permitted beyond 4 percent of tunnel radius, to be on safer side (Singh, 2006). In Fig. 3, characteristics In ofFig. three 3, characteristics types of support of three types are ofplotted. support areThe plotted. support The supportI is rigid I is type, rigid type,thick concrete lining. The support II isthick a combination concrete lining. Theof wire support mesh, II is a combinationshotcrete andof wire rock mesh, bolts. shotcrete It yields and rock at bolts. 12% It support pressure. Support III, steelyields arch at with12% supportwooden pressure. lagging Support begins III, steel reacting arch with to wo theoden deformation lagging begins afterreacting tunnel to closure of 1%. the deformation after tunnel closure of 1%. Here, all the supports are installed at 0.3% closure of Here, all the supportsthe tunnel. are The installed rigid support at 0.3% I does closure not permit of closure the tunnel. more than The 0.5% rigid of the support tunnels inI doesall the not permit closure more than 0.5%four of typesthe tunnels of rock. As in aall result the, it four will betypes loaded of up rock. to 30% As of a insitu result, stress. it willHence be, the loaded required up to 30% of insitu stress. Hence, thecapacity required of the capacity support I is of very the large support else it willI is fail.very Support large II else allows it willclosure fail. up Support to 1.5% of IIthe allows closure up tunnel diameter in the weakest rock simulated in this study. The ground reaction curve along to 1.5% of the tunnelwith support diameter characteristics in the ,weakest help a designer rock to simulated select an effective in this and study. economical The ground support. reaction curve along with support characteristics, help a designer to select an effective and economical support.

Pi P

Fig. 2 Tunnel subjected to hydrostatic stress P and support pressure Pi. Fig. 2: Tunnel Subjected to Hydrostatic Stress P and Support Pressure Pi [395]

e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

100

70 Strength - stress ratio 60 1 50 0.5

40 0.25 0.125 30 I II III

20 Support pressure, % insitueSupport % stress pressure,

0 0.00 0.50 1.00 1.50 2.00 2.50 3.00 % Closure of tunnel

Fig. 3: Tunnel WallFig. Closure 3 Tunnel wallvis-s-vis closure Supportvis-s-vis support Pressure pressure Curves curves for for rock Rock strength Strength-Insitu - insitu stress ratio Stress Ratio 1, 0.5, 1, 0.5,0.25, 0.25, and and 0.125 0.125 and support and Supportcharacteristic Characteristic curves I, II and III. Curves I, II and III On the basis of rock support interaction analysis, characteristics of support and On the basis of rockreinforcement support systeinteractionm can be summarized analysis, as follows:characteristics of support and reinforcement system can be summarized as follows:(1) The rational design of support and reinforcement systems must take into account the interaction between the support or reinforcing elements and the rock mass. 1. The rational(2) design Control of rocksupport displacements and reinforcement is the major role of systemssupport and must reinforcement take into systems. account the interaction Enough displacement must be allowed to enable the rock mass strength to be mobilised between the supportsufficiently or to restrictreinforcing required supportelements loads toand practicable the rock levels mass. (3) However, excessive displacement, which would lead to a loosening of the rock mass and 2. Control of rocka reduction displacements in its load-carrying is the capacity, major must role not ofbe permittedsupport to occur.and reinforcement systems. Enough displacement(4) Themust stiffness be allowed and the time to ofenable installation the of rock the support mass element strength have toan beimportant mobilised sufficiently to restrict requiredinfluence support on this loads displacement to practicable control. levels

3. However, excessive displacement, which would lead to a loosening of the rock mass and a 4. Design of Concrete lining for a vertical shaft reduction in its load-carrying capacity, must not be permitted to occur. A vertical shaft of 7.5 m finished diameter was proposed to be sunk up to 400 m depth 4. The stiffnessthrough and sandstone, the time clay, shaleof installation and coal. Due to of high the insitu support stresses, stresseselement at periphery have ofan the important influence on this displacement control. 6

4. DESIGN OF CONCRETE LINING FOR A VERTICAL SHAFT A vertical shaft of 7.5 m finished diameter was proposed to be sunk up to 400 m depth through sandstone, clay, shale and coal. Due to high insitu stresses, stresses at periphery of the shaft is expected to exceed strength of the rock. This will lead to fracturing and yielding rock at periphery of the shaft wall. A 3D Finite Element model of a quarter of the shaft is shown in Fig. 4. In the FE model, stages of excavation of the shaft and 300 mm thick concrete lining of its wall were simulated. Fracturing and yielding of rock at periphery of the shaft wall was also simulated using non-linear Mohr-Coulomb Elastic Plastic constitutive model. The non-linear simulation of shaft wall displacements, in Fig. 5, shows that effect of shaft excavation face vanishes at a distance of 8 m behind the face, i.e. wall displacement reaches maximum value at one shaft diameter behind the face. Excavated face diameter is 8.1 m. In view of this, we study installation of lining at 2m, 4m and 8 m behind the face at -28 m shown in Figs. 5. The lining at a distance of 2 m from the face will be subjected to higher displacement of the shaft wall compared to one at 4m and 8m. The wall displacement induces stress in the lining. Fig. 6 shows that stress in linings at a distance of 2m from the face is more than that of 4m.

[396] shaft is expected to exceed strength of the rock. This will lead to fracturing and yielding rock at periphery of the shaft wall. A 3D Finite Element model of a quarter of the shaft is shown in Fig. 4. In the FE model, stages of excavation of the shaft and 300 mm thick concrete lining of its wall were simulated. Fracturing and yielding of rock at periphery of the shaft wall was also simulated using non-linear Mohr-Coulomb Elastic Plastic constitutive model. The non-linear simulation of shaft wall displacements, in Fig. 5, shows that effect of shaft excavation face vanishes at a distance of 8 m behind the face, i.e. wall displacement reaches maximum value at one shaft diameter behind the face. Excavated face diameter is 8.1 m. In view of this, we study installation of lining at 2m, 4m and 8 m behind the face at -28 m shown in Figs. 5. The lining at a distance of 2 m from the face will be subjected to higher displacement of the shaft wall compared to one at 4m and 8m. The wall displacement induces stress in the lining. Fig. 6 shows that stress in linings at a distance of 2m from the face is more than that of 4m. Rock Support Interaction Analysis and Design of Support

Concrete lining

Shaft face

Clay layer

Fig. 4 3D FE Fig.model 4: of 3D quarter FE ofModel the shaft of Quarter of the Shaft Fig. 5 show plots of displacement (closure) of wall of the shaft at different stages of excavation. It shows that at the face, wall closureFig. 5 show is almost plots of displacementnegligible (closure)and gradually of wall of increasesthe shaft at different behind stages from of the face. The closure excavation. It shows that at the face, wall closure is almost negligible and gradually increases is stabilized afterbehind one diameterfrom the face. behind The closure the isface. stabilized Thus, after the one corediameter of behithend rock the face. at the Thus, face the coretends to support the shaft wall up to distanceof the rock ofat theone face diameter tends to support behind the shaft the wallface. up Afterwards,to distance of one it diametersupporting behind effect the vanishes. Thus, plot of shaft wallface closure. Afterwards vis-à-vis, it supporting distance effect of vanishes. the face Thus, can plot beof shaft taken wall asclosure ground vis-à- visreaction distance curve similar to Fig.3. Further, weof concludethe face can bethat taken stability as ground of reaction core of curve the similar face tois Fig.3.very Further,important we conclude in maintaining that stability of the Unstable and failedstability rock of corecore ofat the the face face is very will important not be inable maintaining to provide stability support of the wallto the and wall. tunnels. This has wallled to and severe tunnels. failure Unstable and collapse and failedof cavity rock at core the faceat the and face behind will it.not be able to provide support to the wall. This has led to severe failure and collapse of cavity at the face and behind it. 7

Shaft

Face at 328 m depth

Fig. 5: Shaft Wall Displacement Without Lining. Blue Vertical Line- Shaft Face Position at -328 m; Red Vertical Fig 5. Shaft wallLines-Position displacement ofwithout Concrete lining. Lining Blue a verticalDistance line of -2, shaft 4 and face 8 m position from the at Face-328 m; Red vertical lines- position of concrete lining a distance of 2, 4 and 8 m from the face.

[397]

Linings installed: 2 m behind the face 4 m behind the face

Fig. 6. Maximum compressive stress in lining.

Unstable and failed rock core at the face will not be able to provide support to the wall. This has led to severe failure and collapse of cavity at the face and behind it.

Shaft

Face at 328 m depth

Fig 5. Shaft wall displacementnd without lining. Blue vertical line- shaft face position at -328 m; Red vertical lines-e-Book: position 2 Nationalof concrete Conference lining on a Recentdistance Advances of 2, 4in andCivil Engineering8 m from the(RACE-II) face.

Linings installed: 2 m behind the face 4 m behind the face

Fig. 6. Maximum compressiveFig. stress 6: Maximum in lining. Compressive Stress in Lining

5. FIELD OBSERVATION OF STRESSES IN SHAFT WALL LINING 8

Kaeser, et al., (1982) reported monitoring by measuring rock mass displacement around the shaft wall and the stress build up in cast-in-place concrete lining which occurred during advance of a 235 m deep, 4.3 m dia shaft at Kip mine in Canada. The shaft was constructed in clay shales using conventional drilling and blasting. The lining construction generally followed one to two shaft diameter behind the shaft bottom. On average zero straining or even extensional straining were observed at all the locations except at the lowest instrumented ring at 180 m depth. Finally, the study concluded that a shotcrete layer of less than 10 cm thickness would theoretically be sufficient to support the rock if installed at the same distance two shaft diameter from the shaft bottom. Tsusaka, et al., (2012) reported circumferential stress distribution in a concrete lining and displacement of rock around shaft wall induced by shaft excavation at Horonobe, Underground Research Laboratory, Japan. Field measurements of the lining stress and rock displacement were conducted between 218m and 220m in depths during excavation of a 6.5m diameter access shaft. The shaft was sunk through mudstones having Uniaxial compressive strength 10-40 MPa. The main support members were 2–4m long rock bolts, steel arch ribs and a 400mm thick concrete lining. The shaft excavation was done using a cyclical procedure that essentially consisted of four repetitive steps.In any given initial state, the shaft bottom, i.e., the excavation face, is approximately 1m below the lower edge of the concrete lining. Measured circumferential stresses in lining was 2-6 MPa in upper part of the lining and 10-14 MPa in lower part of the lining as shown in Fig. 6. Kaeser, et al., (1982) and Tsusaka, et al., (2012) corroborate with our analysis of induced stresses in lining behind the face in shaft.

6. PRINCIPLES OF TUNNEL STABILIZATION AND LINING DESIGN (KUESEL, 1997) 1. The most important part of the tunnel lining is the ground that surrounds it. 2. The most important component of the ground is the groundwater. 3. The most important element of lining construction is to secure full, continuous contact between the lining and the ground.

[398] Rock Support Interaction Analysis and Design of Support 4. The objective is to stabilization ground movement, not to carry ground loads. 5. The most efficient tunnel stabilization and lining system is one that mobilizes the strength of the ground by permitting controlled ground deformation. 6. Axial stiffness of the lining permits it to distribute nonuni-form ground loads by mobilizing passive pressure from the surrounding ground, and it can thereby modify ground deformations. 7. Flexural stiffness of the lining is inefficient (and usually in-effective) in modifying ground deformations. 8. For multistage linings, the initial construction support is very flexible compared with the ground, and it can absorb large flexural deformations associated with redistribution of ground stresses. 9. If the installation of secondary linings is deferred until the ground has stabilized, they will not be subject to significant flexural deformations. 10. Single-stage linings (generally segmental) are flexible with respect to the ground, except for very soft clay. Such linings should preferably be thin, to minimize parasitic flexural stresses resulting from ground deformations. 11. Selection of the type of lining depends on excavation methods that are suited to the ground characteristics, of which stand-up time is usually most significant. Timing of lining installation can substantially affect the magnitudes of ground deformation and lining loads. 12. Dimensions of the lining are controlled by considerations of water sealing, constructability, and facility usage, rather than by ground loads. 13. Estimates of ground loads and passive pressures are subject to wide uncertainty owing to redistribution of in situ stresses related to ground deformations before and after lining installation, and construction procedures such as contact grouting. Loads and pressures vary along the length of the tunnel owing to variations in geology and in construction proficiency. 14. The largest loads on the lining may come from construction processes such as shield jacking loads and contact grout pressures. 15. The precision of mathematical analyses of stresses in structural rings vastly exceeds the precision of estimation of the loads and support conditions on which the analyses are based. 16. A tunnel liner ring confined by the surrounding ground cannot deform in flexure independently from the ground. Independent structural failure in flexure is impossible unless there are unfilled voids behind the lining. 17. The structural performance of lining elements installed before ground deformations have been stabilized can be appraised by analyzing them for axial thrust plus an imposed deformation measured by an arbitrary change in lining diameter. Appropriate design values may be based on prior tunneling experience in similar ground, may be specified as construction requirements, and may be verified by instrumentation monitoring. 18. Lining elements installed after the ground deformations have been stabilized can be analyzed for axial loads only, plus allowances for anticipated effects of future construction and long-term ground squeezing effects, if appropriate.

[399] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) REFERENCES [1] Singh, B. and Goel, R.K. (2006). Tunnelling in weak rocks. - (Elsevier geo-engineering book series; v. 5), 1st Ed, 2006, p. 509. [2] Jaeger, J. C. And Cook NGW (1979), Fundamentals of Rock Mechanics, 3rd Ed (1979), p. 593. [3] Kaiser P.K., et al. (1982). Performance of a shaft in weak rock (BEARPAW shale). In ISRM symposium / Aachen / 1982.05.26- 28. Pages 613–622. [4] Kuesel, T.R. (1997). Tunnel stabilisation and lining. In Tunnel Engineering Handbook, Eds. Bickel, J.O et al., CBS Publication, 2nd Ed., PP. 80–96. [5] Tsusaka, K. et al. (2012). A study on mechanical behaviors of concrete lining and rock caused by shaft sinking at the Horonobe Underground Research Laboratory. In Harmonising Rock Engineering and the Environment – Qian & Zhou (Eds) © 2012 Taylor & Francis Group, London, ISBN 978-0-415-80444-8. Pages 305-308.

[400] Unmanned Aerial Vehicles and Artificial Intelligence Tools for Wetland Monitoring

Dr. Bushra Zaman Adjunct Professor, Department of Civil & Environmental Engineering, College of Engineering, Utah State University, Logan, Utah, USA Consultant (Academics/ Institutional Development), State Project Implementation Unit, Bihar, World Bank – MHRD TEQIP-III Project

ABSTRACT Small Unmanned Aerial Vehicles are being increasingly used for environmental applications and its use is relatively new for specific wetland monitoring. Artificial intelligence tools like support vector machines, artificial neural networks and relevance vector machines have been successfully used for land cover classification. However, the full potential of using information from very-high resolution hyperspectral data from small unmanned aerial vehicles (SUAV), along with artificial intelligence techniques, especially the multiclass relevance vector machine, for wetland change monitoring, has not been realized yet. These tools have never been in concert for wetland monitoring. Due to the complexities and diversity of landcover/landuse of wetlands, simple pixel-based methods are not appropriate for the image classification of wetlands. A more robust method using ancillary data is required to reduce classification errors. To this extent, a study is proposed which analyses the spread of invasive species in one of the most important wetlands of Bihar. Kabar tal wetland in Begusarai, Bihar, is known for its rich biodiversity and it houses 106 species of resident, 59 species of migratory birds and 41 species of fishes. The wetland has one of South Asia’s largest freshwater ox- bow lakes and is the single biggest source of irrigation for rice cultivation and fishing. However, the wetland is facing rampant and unsustainable exploitation. The invasive weed species is sucking the wetland dry and is also a nuisance for water quality. A rapid change in surface water regime is also being observed. This study proposes to map the kabar tal wetland using UAV imagery and to develop a new AI tool, called the hierarchical multi-class relevance vector machine (HMCRVM) model. This new AI tool completes classification in two steps wherein, in the first phase it will conduct a binary classification with weed/no weed and in second phase, it will conduct a multiclass classification on the output image of the first phase and will figure out the various species of weeds. The training and validation of the study/model will require ground data collection. The results would be imported into GIS for spatial analysis and to produce the weed extent maps. Hence the combined used of SUAV and AI tool will produce results which will aid the decision support system to either control its growth or to eradicate it. Keywords: Wetland Monitoring, Remote Sensing, GIS, RVM, Hyperspectral, Water UAV, Supervised Classification

[401] Changing Nature of Disaster Risk in the 21st Century: Evolving Role of Engineers in Disaster Management

Paras Nath Rai IPS (Retd.) Member, Bihar State Disaster Management Authority, Bihar, India

ABSTRACT Disaster for most of us has been flood and earthquake. However, the entire disaster profile has changed and today disaster management encompasses many other natural and human induced disasters which includes pollution, water scarcity, building collapse, Boat tragedy, Mass Gathering-Stampede, Fire, Sanitation, Urban flooding, Road accidents, etc. Accordingly, the scope of disaster management has also expanded. One needs to appreciate that many of these disasters are preventable and if not, their effects could be mitigated. Now we have to look to holistic approach involving preparation, prevention, mitigation, response and recovery. Therefore, disaster management is no longer limited to response. It has undergone a paradigm shift from pure rescue and relief to disaster risk reduction where civil engineers have a significant role. Climate change is adding new and more intractable dimensions to the problem of risk. It is accepted that climate change will alter the severity, frequency and complexity of climate related hazards. Now we are witnessing increasing trend of hydro-meteorological disasters due to climate change and extreme weather. The 2019 super cyclone in Odisha and Bihar flood 2017, in Araria and Kishanganj districts among others are instances of extreme weather. A very significant dimension that may attract the attention of civil engineers is that, while there may be lesser number of deaths, there is escalating economic losses. As population and economy continue to grow, larger number of people and infrastructuresare likely to be impacted in hazard prone areas. The reduced loss of human lives points towards a better preparedness, but at the same time the escalating economic losses due to damaged infrastructure is because of poor disaster risk reduction/mitigation measures. This makes the job of disaster management managers increasingly difficult. This could be a challenge for civil engineers.

It needs to be appreciated that rapid but unplanned and unorganized urbanization has increased the vulnerability. There is poor compliance of National Building Code and other relevant regulations, one because of poor awareness among all stakeholder and two willful non-compliance/neglect of basic safety requirement. These aspects throw challenges to the engineering community as well as disaster management community.Therefore, all future projects both private and government must include disaster sensitive evaluation as part of project proposal.

●● Disaster for most of us has been flood and earthquake. However the entire disaster profile has changed and today disaster management encompasses many other natural and human induced disasters which includes pollution, water scarcity, building collapse, Boat tragedy, Mass gathering-Stampede, Fire, Sanitation, Urban flooding etc. Accordingly the scope of disaster management has also expanded. Road accidents have emerged as major disaster as 6700 were killed in Bihar in 2018.

[402] Changing Nature of Disaster Risk in the 21st Century: Evolving Role of Engineers in Disaster Managemen One needs to appreciate that many of these disasters are preventable and if not their effects could be mitigated. To give an example, 100s of acres of crops and large number of hutments are destroyed in fire every year in Bihar. Not to mention of loss of lives and livestock. All because of little or no investment on mapping of water resources or investment on creation of water resources among other measures. Now we have to look to holistic approach involving preparation, prevention, mitigation, response and recovery. Therefore disaster management is no longer limited to response. It has gone undergone a paradigm shift from pure rescue and relief to disaster risk reduction where civil engineers have a significant role. ●● Now we are witnessing whole lot of disasters due to climate change and extreme weather. Processes of climate change are adding new and more intractable dimensions to the problem of risk. It is accepted that climate change will alter the severity, frequency and complexity of climate related hazards. The 2019 super cyclone in Odisha and Bihar flood 2017, in Araria and Kishenganj districts among others are instances of extreme weather. Infrastructure worth thousands of crores was lost during these disasters. There is increasing trend of hydro-meteorological disasters.

Fig. 1 A very significant dimension that may attract the attention of civil engineers is that, while there may be lesser number of deaths, there is escalating economic losses. This is more so in poorer countries. Accordingly as population and economy continue to grow, larger number of people and infrastructure is likely to be impacted in hazard prone areas. The reduced loss of human lives points towards a better preparedness but at the same time the escalating economic losses due to damaged infrastructure is because of poor disaster risk reduction/mitigation measures. This makes the job of disaster management managers increasingly difficult. This could be a challenge for civil engineers.

[403]  A very significant dimension that may attract the attention of civil engineers is that, while  thereA very may significant be lesser dimension number of that deaths may, thereattract is theescalating attention economic of civil engineerslosses. This is that,is more while so inthere poorer may becountries. lesser number Accordingly of deaths as , populationthere is escalating and economy economic continue losses. toThis grow, is more larger so innumber poorer of countries.people and Accordingly infrastructure as ispopulation likely to beand impacted economy in continuehazard prone to grow, areas. larger The numberreduced ofloss people of human and infrastructurelives points towards is likely a betterto be preparednessimpacted in hazardbut at theprone same areas. time The the reducedescalating loss economic of human losses lives due points to damagedtowards ainfrastructure better preparedness is because but ofat thepoor same disaster time riskthe escalatingreduction/mitigation economic lossesmeasures. due toThis damaged makes infrastructure the job of disaster is because management of poor disaster managers risk increasingly difficult. This could be a challenge for civil engineers. reduction/mitigatione-Book: 2ndmeasures. National Conference This makeson Recent the Advances job inof Civil disaster Engineering management (RACE-II) managers increasingly difficult. This could be a challenge for civil engineers.

Fig. 2

Fig. 3 With regard to specific role of civil engineers, it needs to be appreciated that rapid but unplanned and unorganized urbanization has increased the vulnerability of people living in cities. The Surat incident is an example of unsafe environment. Governments, and people are spending thousands of crores in

[404] Changing Nature of Disaster Risk in the 21st Century: Evolving Role of Engineers in Disaster Managemen construction of roads and bridges, rail including Metro- Length of metro lines will go up 6 times by 2025, smart city, airports even in small places, multiplexes, apartments, huge hospitals, water supply, energy and communication sectors. Highways length will go up 1.5 times by 2025. Electricity generation capacity will almost double by 2025. Is Vulnerability assessment mandatory of DPR? As it is there is poor compliance of National Building Code and other relevant regulations, one because of poor awareness among all stakeholder and two willful non compliance/neglect of basic safety requirement. The share of houses which re prone to earthquake is growing as most are not aware of earthquake safe building construction. These aspects throw challenges to the engineering community as well as disaster management community. Therefore all future projects both private and government must include disaster sensitive evaluation as part of project proposal otherwise investments will be washed away, banks will have mounting NPAs. And of course it is a well known fact that rebuilding is far more expensive and painful- Kosi, Uttarakhand, Nepal. The final word could be DO NOT CREATE FUTURE RISK.

[405] Elements of Comprehensive Mobility Plan for Patna 2018

Sanjeev Sinha Professor, Department of Civil Engineering, National Institute of Technology Patna, Bihar, India

ABSTRACT The CMP aims to provide a long-term strategy for the desirable mobility pattern of a city’s populations. Comprehensive Mobility Plan (CMP) is a vision statement of the direction in which urban transport in the city should grow. It is a long-term vision for desirable accessibility and mobility pattern for people and goods in the city to provide, safe, secure, efficient, reliable and seamless connectivity. It should cover all elements of urban transport under and integrated planning process. The basic aim of any CMP is for the improvement in mobility for all socio-economic groups and genders. Improvement in air quality of Sustainable Urban Transport scenario with reference to the Business as usual (BAU) scenario. It aims to enhance safety and security for pedestrians, non-motorized traffic and habitability in the city. It promotes sustainable transport mode share and a decrease in private motor vehicle use. It is always an integral part of master plan. The CMP of Patna was prepared accordance with the Toolkit for Comprehensive Mobility Plan (CMP) 2014 published by the Ministry of Housing and Urban Affairs, study of Service Level Benchmarks as per Ministry of Housing and Urban Affairs Handbook on Service Level Benchmarks for Urban Transport and Appraisal Guidelines for Metro Rail Project Proposals (2017), and Metro Policy 2017. The plan includes plan for public transportation, pedestrian facilities, non-motorized transportation, road development, construction of roads, fly-overs, freight movement management etc.

[406] Mechanical Properties of Fibre Reinforced Self Compacting Concrete

Brajkishor Prasad1, Amit Patel2 and Prince Singh3 1Associate Professor, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India 2M.Tech. Student, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India 3Research Scholar, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India E-mail: [email protected]

ABSTRACT Self-compacting concrete (SCC) have a lot of advantages over normal concrete and hence can be used in some special pouring conditions; the use of steel fibres can further enhance its mechanical properties. Steel fibres act as a bridge to restrict the propagation of cracks and also improve several characteristics of the concrete. In this study mix design, workability and the mechanical properties of steel fibre reinforced self-compacting concretes (SFRSCC) are determined. In the present study, self-compacting concrete of grade M40 was designed and the cube, cylinder and prism specimens have been cast and then tested to get the compressive strength, split tensile strength and flexural strength respectively of the concrete. These self-compacting mixes were designed replacing 26% of cement by weight with Class-F fly ash. Fibres with three different aspect ratios i.e. 25, 50 and 60 were used and there percentage of volume fraction were taken i.e. 0.5%, 1.0% and 1.5% respectively of total volume of concrete. Slump flow time and diameter test, J-Ring test, and L-Box test were performed to determine the properties of the concrete in fresh state. Also the mechanical properties of SCC and SFRSCC have been determined and compared in order to get an idea of effect of fibres.

1. INTRODUCTION Self-Compacting Concrete (SCC) was first developed to improve the durability stability of concrete structures in Japan in 1988. It is considered as a concrete which can be placed and compacted under its own weight with little or no external effort, and which is at the same time cohesive enough to be handled without segregation or bleeding. Use of self-compacting concrete (SCC) in the construction industry has grown significantly due to its technical advantages. Generally, SCC is achieved using new generation superplasticizers to reduce the water–binder ratio Main benefits of using it are (i) reducing the noise caused by vibration; (ii) reducing the cost of placement; (iii) increasing the speed of construction; and (iv) decreasing the number of skilled workers. Such concrete requires a high slump that can easily be achieved by adding super plasticizer to a concrete mixt. However, for such concrete to remain cohesive during handling operations, special attention has to be paid to mix proportioning. In addition, supplementary cementitious or inert materials such as limestone powder, natural pozzolans, and fly ash is also used to increase the viscosity and reduce the cost of SCC. Among these materials fly ash, a by-product of thermal power plants, has been reported to improve the mechanical properties and durability of concrete when used as a cement replacement material [4, 9]. Researchers have investigated the behaviour of SCC with several types of pozzolanic materials to replace as a part of the cement. Siddique [19] reported that, the use of mineral admixtures increase the slump of the concrete mix without increasing its cost, while reducing the dosage of superplasticizer. Previous studies have shown that the mixes containing fly ash show lower compressive strength values at early ages. This situation was caused by the slow pozzolanic reaction between the cement and fly ash [20]. Fly ash is usually separated at the

[407] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) power plants and high quality (fine) fly ash meeting the fineness requirement of ASTM C 618 can be used in producing blended cements or added as a separate ingredient at the ready mixed concrete batching plants. In addition to this fine fly ash, there are vast amounts of substandard (coarse) fly ash that can be utilized in the concrete industry. In this paper, an application of a fly ash will be presented on SCC incorporating steel fibre reinforcement. However, hardened self-compacting concrete is still as brittle as normal concrete and has a poor resistance to crack growth. To improve the post-peak parameters of SCC the steel fibres are added. Analysing of the influence of fibres on workability and durability of the parameters of concrete is one of new tendencies in research of self-compacting concrete. The research upon the influence of steel fibres of various geometric parameters was presented to determine the impact of its volume fraction, the length and the shape on rheological and mechanical properties of self-compacting concrete. Previous investigations show that the use of steel fibres in SCC is feasible. In these mixtures, steel fibres can decrease workability of SCC as the fibre amount and slenderness ratio (length/diameter) increase. The incorporation of fibres in concrete improves mechanical properties of concrete such as ductility, toughness, tensile strength, impact resistance and fatigue. The objective of this study is to assess the effects of steel fibres on the fresh and hardened properties of SCC. Three different sizes of steel fibres were used at different proportions in making the concrete. Total mass of cementitious materials was taken as 460 kg/m3. The commercially available chemical admixtures used in this study included a polycarboxylic-based superplasticizer (SP).

2. MATERIALS USED

2.1 Cement The cement used in this study is commercially available as Portland slag cement manufactured by Lafarge Company confirming to IS 455:2015.

Table 2.1: Physical Properties of Cement Properties Values Remarks Consistency 33 % IS:4031–Part–IV–1988 Fineness 1.4 % IS:4031–Part–I–1988 Specific gravity 2.91 IS:4031– Part–XI–1988 Initial setting time 80 min. IS:4031–Part–V–1988 Final setting time 5 hr. 20 min. IS:4031–Part–V–1988 3 days 16.67 N/mm2 Cube strength 7 days 21.02 N/mm2 IS:4031–Part–VI–1988 28 days 33.52 N/mm2

2.2 Fly Ash Locally available Class-F fly ash procured from Usha Martin Limited Company was used in this study. The fly ash had a specific gravity of 2.11.

Table 2.2: Physical Properties of Fly Ash Properties Values Colour Dark grey Bulk density 998 kg/m3 Specific gravity 1.98 Fineness 1.4% Average partial size* 6.92 µm *Source: Usha Martin Limited Company

[408] Mechanical Properties of Fibre Reinforced Self Compacting Concrete

Table 2.3: Chemical Properties of Fly Ash

Different Ingredient SiO2 AlO3 Fe2O3 CaO MgO SO3 LIO % weight 55.198 22.62 6.98 8.31 1.056 1.538 2.42 Source: Usha Martin Limited Company

2.3 Fine Aggregate Locally available sand (passed through 4.75mm IS sieve) from the River Kharkhai through 4.75mm IS sieve was used in this research work. This sand is widely used and is free from organic particles and has a limited content of silt and clay and is hence very suitable for construction purposes.

Table 2.4: Physical Properties of Fine Aggregate Properties Values Remarks Fineness modulus 2.7 % IS 383–2016 Zone II IS 383–2016 Specific gravity 2.63 IS:2386–Part III–1963 Water absorption 1.4% IS:2386–Part III–1963 Bulk density in loose state 1580 Kg/ IS:2386–Part III–1963 Bulk density in compacted state 1663 Kg/ IS:2386–Part III–1963

2.4 Coarse Aggregate Crushed granite aggregate with a maximum size of 16mm available from local sources was used in this study.

Table 2.5: Physical Properties of Coarse Aggregate Properties Values Remarks Specific gravity 2.73 IS:2386–part III–1963 Water absorption 0.6 % IS:2386–Part III–1963 Fineness modulus 7.36 IS:383–2016 Impact value 7.8 % IS:2386–Part IV–1963 Crushing value 12.9 % IS:2386–Part IV–1963 Bulk density in loose state 1733 kg/ IS:2386–Part III–1963 Bulk density in compacted state 1840 kg/ IS:2386–Part III–1963

2.5 Superplasticizer AURAMIX 300 was used as admixture in this work. It was procured from FOSROC Chemicals based in Kolkata.

Table 2.6: Physical Properties of Superplasticizer Properties Values Specific gravity 1.14 Appearance Light yellow coloured liquid Solid content – – – pH 6 Volumetric mass @ 20°C 1.05 kg/litre Chloride content* Nil Alkali content* Typically less than 1.5 g Na2O equivalent / litre of admixture.

* Provided by Fosroc chemicals [409] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.6 Steel Fibre Steel fibre of diameter 0.5mm was used in this research work. The main variables used in the study are three different aspect ratios (25, 50 and 60) and the corresponding lengths are 12.5mm, 25 mm and 30mm respectively. Three different values of percentage of weight fraction of steel fibres (0.5%, 1.0% and 1.5%) were also taken.

Fig. 3.1: Crimped Steel Fibre with Different Aspect Ratio

Table 2.7: Properties of Steel Fibres Sl. Length (L) Diameter (D) Aspect Ratio Number of Specific Tensile Strength No. mm mm (L/D) Fibers (per Kg.) Gravity (N/) 1. 12.5 0.5 25 34592 2. 25 0.5 50 18842 7.85 1050 3. 30 0.5 60 16267

3. EXPERIMENTAL PROGRAM Concrete mixes with the different proportions as provided in Table 4.1, were prepared. SCC was cast replacing 26% of cement with fly ash by volume (A0V0). All the other mixes were cast using the same mix ratio that contained different volume of steel fibre and aspect ratios. These mixes are designated as A1V1, A1V2, A1V3, A2V1, A2V2, A2V3, A3V1, A3V2 and A3V3 indicating the three different values of aspect ratios (A1=25, A2=50 and A3=60), and three different values of percentage of volume fraction (V1=0.5%, V2=1% and V3=1.5%) of steel fibre incorporated in the concrete. For all the mixes, the total amount of cement, fly ash, fine & coarse aggregate and water was kept constant. To obtain the SCC characteristics, the optimum quantity of superplasticizer (SP) was kept constant as 0.8% of the total weight of the powder (cement + fly ash) content.

Table 3.1: Mix Proportions of Different Concrete Mixture Sl. MIX ID A V (%) Cement Fly Ash Water W/P F.A. C.A. SP No. (Kg/) (Kg/) (Kg/) (Kg/) (Kg/) (Kg/) 1. SCC – – 460 160 235.6 0.38 750 900 4.96 2. A1V1 25 0.15 460 160 235.6 0.38 750 900 4.96 3. A1V2 50 0.3 460 160 235.6 0.38 750 900 4.96 4. A1V3 60 0.45 460 160 235.6 0.38 750 900 4.96 5. A2V1 25 0.15 460 160 235.6 0.38 750 900 4.96 6. A2V2 50 0.3 460 160 235.6 0.38 750 900 4.96 7. A2V3 60 0.45 460 160 235.6 0.38 750 900 4.96 8. A3V1 25 0.15 460 160 235.6 0.38 750 900 4.96 9. A3V2 50 0.3 460 160 235.6 0.38 750 900 4.96 10. A3V3 60 0.45 460 160 235.6 0.38 750 900 4.96

[410] Mechanical Properties of Fibre Reinforced Self Compacting Concrete 4. RESULT AND DISCUSSION

4.1 Fresh Concrete Properties The results of fresh concrete tests are shown in Table 4.1, which included the slump flow diameter and time, L-Box ratio test and J-Ring test. As seen in that the slump flow diameters of concrete mixtures were in rang of 710–655 mm and the time was varies 3–4.8 sec. the J-ring were in the range of 3–9.5 mm, the L-box ratio test values were in the range of 0.95–0.82. Based on above results concrete mixtures were consider as SCC. In all of the SCC mixtures, there was no segregation of aggregate near the edges of the spread-out concrete and bleeding as observed from the slump flow test.

Table 4.1: Properties of Fresh Concrete of Different Mix S. No. Mix ID Slump Flow Test (mm) Time (Sec.) J-Ring Test (mm) L-Box Test 1. SCC 710 3 3 0.95 2. A1V1 705 3.4 3.5 0.92 3. A1V2 695 3.9 5 0.88 4. A1V3 690 4.2 7 0.86 5. A2V1 685 4.1 6 0.87 6. A2V2 675 4.3 8 0.85 7. A2V3 660 4.7 9 0.82 8. A3V1 680 4.1 6 0.86 9. A3V2 665 4.5 8.5 0.84 10. A3V3 655 4.8 9.5 0.82 From table 5.3, it can be noticed that SCC is more flowable and has better self-compacting ability as compared to the other concretes as it has the highest slump flow, less time and less J-ring value as well. Due to spherical shape and smooth surface of the fly ash, the workability of concrete mixtures improved considerably for a concrete mix with lower water content. The addition of steel fibres did not affect the water requirement of the mixture but prevented the movement of aggregate; hence, it affected the fresh properties of the concrete mixtures. For comparing the effect of different aspect ratios and different volumes of steel fibres on different fresh properties of concrete; the amount of cement, fly ash, w/p, fine aggregate, coarse aggregate and SP were kept constant in SFRSCC. It was observed that with the increase in the aspect ratio and volume of steel fibre, slump flow diameter decreases, time increases, J-ring value increases, and L-box ratio decreases. The mixture A3V3 had steel fibre of larger length and volume percentage as compare to other SFRSCC, due to which its fresh properties were found to be the worst among all.

(i) Flow Table Test (ii) J-Ring Test (iii) L-Box Test

Fig. 4.1: Workability Tests Performed on SCC & FRSCC [411] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

4.2 Hardened Concrete Properties

4.2.1 Effect of Steel Fibre on Mechanical Properties The results of hardened concrete tests are shows in Table 4.2, which included the 28 days test results of compressive, splitting tensile strength and flexural strength tests performed on the concrete specimens. The effect of aspect ratio and percentage volume of steel fibre in SFRSCC the 28 days mechanical properties results are present in Fig. 4.2, Fig.4.3 and Fig.4.4.

Table 4.2: Mechanical Properties of Different Mix S. No. Mix ID Compressive Strength (N/) Flexural Strength (N/) Split Tensile Strength (N/) 1. NC 49.66 8.13 4.84 2. SCC 40.03 6.93 4.28 3. A1V1 3. A1V1 40.79 40.79 7.06 7.06 4.34 4.34 4. A1V2 41.09 7.33 4.42 4. A1V2 3. A1V1 41.09 40.79 7.06 7.33 4.34 4.42 5. A1V3 5.4. A1V3A1V2 41.88 41.8841.09 7.467.33 7.46 4.514.42 4.51 6. A2V1 43.63 8.00 4.90 6. A2V1 5. A1V3 43.63 41.88 7.46 8.00 4.51 4.90 7.6. A2V2A2V1 45.1143.63 8.138.00 4.964.90 7. A2V2 45.11 8.13 4.96 8.7. A2V3A2V2 46.0245.11 8.408.13 5.034.96 8. A2V3 9.8. A3V1A2V3 46.02 44.1146.02 8.278.40 8.40 4.985.03 5.03 9. A3V1 10.9. A3V2A3V1 44.11 45.7444.11 8.538.27 8.27 5.044.98 4.98 10. A3V2 11.10. A3V3A3V2 45.74 46.9745.74 8.678.53 8.53 5.175.04 5.04

11. A3V3 11. A3V3 46.97 46.97 8.67 8.67 5.17 5.17 V1 V2 V3

48 V1 V2 V3 4748 4647 4546 4445 4344 4243 4142 4041

comperessive strength (N/mm²) 3940

comperessive strength (N/mm²) 3839 3738 37 A1 A2 A3 A1 A2 A3 Aspect ratio Aspect ratio

Fig 4.2: Variation in compressive strength for different Aspect ratio Fig. 4.2:Fig Variation4.2: Variation in inCompressive compressive strength Strength for differentfor Different Aspect Aspect ratio Ratio

V1 V2 V3 V1 V2 V3 9 9

8.5 8.5

8 8

7.57.5

7 7 Flexural Strength (N/mm²) Strength Flexural Flexural Strength (N/mm²) Strength 6.5Flexural 6.5

6 6 A1A1 A2A2 A3 AspectAspect ratio ratio

Fig.Fig Fig4.3: 4.3 4.3: Variation:Variation Variation in in Flexural FlexuralFlexural strength strength Strength forfor differentdifferent for Different AspectAspect ratioAspect Ratio [412]

Mechanical Properties of Fibre Reinforced Self Compacting Concrete

V1 V2 V3

5.5

4.5 Split tensile strength

4 A1 A2 A3 Aspect ratio

Fig.Fig 4.4: 4.4: VariationVariation inin Splitsplit tensileTensile strengt Strengthh for for different Different Aspect Aspect ratio Ratio

Fig 4.5 Cracking pattern of different specimens

Fig. 4.5: Cracking Pattern of Different Specimens As evident from the figure, the mechanical properties of SFRSCC increased with the As evident fromincrease the figure, in both theaspect mechanical ratio and percentage properties volume of SFRSCCof steel fibres. increased These fibres with were the ableincrease in both aspect ratio andto percentage delay the formation volume of of micro steel-cracks fibres. and These if the fibres crack weregenerate abled too, to delaythey prevent the formationed the of micro- cracks and if thepropagation crack generated of cracks uptoo, to athey certain prevented extent. It wasthe noticedpropagation that the loadof cracksing capacity up to of athe certain extent. It was noticed thatconcrete the alsoloading increase capacityd with the of increase the concrete in fibre volumealso increased fraction. Thewith increase the increase in the fibre in fibre volume fraction. The increasevolume significantlyin the fibre increased volume the significantly fracture energy increased of concretes the fracture[10]. Short energy fibres hadof concretesa [10]. less effect on the fracture energy of concretes as compare to long fibres. One of the other Short fibres had a less effect on the fracture energy of concretes as compare to long fibres. One of the reasons for the enhancement of mechanical properties of concrete is, that after cracking of other reasons forbrittle the matrices, enhancement ductility ofof mechanicalfibres helped propertiesto carry and oftransfer concrete the l oadsis, that to other after fibres; cracking of brittle matrices, ductilityhence of fibresit help edhelped in making to carry the andconcrete transfer more thecohesi loadsve and to othermaintaining fibres; the hence integrity it helped of in making the concrete moreconcrete cohesive matrix. and maintaining the integrity of concrete matrix.

5. CONCLUSIONConclusion 1. The mechanical1. The mechanicalproperties properties i.e. compressive, i.e. compressive split ,tensile split tensile and andflexural flexural strength strength of of SFRSCC was found to be higherSFRSCC than was thatfound of to SCC. be higher than that of SCC. 2. At constant w/p ratio & superplasticizer content, a significant reduction in the flow-ability of SFRSCC was noticed with the percentage of fibre which can be compensated by increasing the dose of superplasticizer.

3. The addition of fly ash in SCC improved the workability of concrete. 4. The strength of SFRSCC increased with the increase in aspect ratio and volume content of fibres.

[413] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) REFERENCES [1] Steffen Grunewald, Joost C. Walraven, “Parameter-study on the influence of steel fibres and coarse aggregate content on the fresh properties of self-compacting concrete”, Volume 31, Issue 12, December 2001, Pages 1793-1798 [2] Mustafa Sahmaran, Alperen Yurtseven, I. Ozgur Yaman, “Workability of hybrid fibre reinforced self-compacting concrete”, Volume 40, Issue 12, December 2005, Pages 1672-1677 [3] A.M. Brandt, V.C. Li and I. H. Marshall, “The rheological properties of fresh steel fibre reinforced self-compacting concrete”, Warsaw, October 23-25, 2006 [4] Mustafa Sahmaran, I. Ozgur Yaman, “Hybrid fibre reinforced self-compacting concrete with a high volume coarse fly ash”, Volume 21, Issue 1, January 2007, Pages 150-156 [5] Eduardo N. B. Pereira, Joaquim A. O. Barros, and Aires Camoes “Steel Fibre-Reinforced Self-Compacting Concrete Experimental Research and Numerical Simulation”, Journal of Structural Engineering, 2008, 134(8): 1310-1321 [6] Y. Ding, S. Liu, Y. Zhang, A. Thomas, “The investigation on the workability of fibre cocktail reinforced self-compacting high performance concrete”, Construction and Building Materials 22 (2008) 1462–1470 [7] Y. Ding, Y. Zhang, A. Thomas, “The investigation on strength and flexural toughness of fibre cocktail reinforced self- compacting high performance concrete”, Construction and Building Materials 23 (2009) 448–452 [8] Amr S. El-Dieb, “Mechanical, durability and microstructural characteristics of ultra-high-strength self-compacting concrete incorporating steel fibres”, Volume 30, Issue 10, December 2009, Pages 4286-4292 [9] B. Krishna Rao, “Steel fibre reinforced self compacting concrete incorporating class f fly ash”, Vol. 2(9), 2010, 4936-4943 [10] Burcu Akcay, Mehmet Ali Tasdemir, “Mechanical behaviour and fibre dispersion of hybrid steel fibre reinforced self- compacting concrete”, Volume 28, Issue 1, March 2011, Pages 287-293 [11] V.M.C.F. Cunha, J.A.O. Barros, J.M. Sena-Cruz, “An integrated approach for modelling the tensile behaviour of steel fibre reinforced self-compacting concrete”, Cement and Concrete Research 41 (2011) 64–76 [12] Liberato Ferrara, Patrick Bamonte, Alessio Caverzan, Abdisa Musa, Irem Sanal, “A comprehensive methodology to test the performance of Steel Fibre Reinforced Self-Compacting Concrete (SFR-SCC)”, Construction and Building Materials 37 (2012) 406–424 [13] M. Pajak, T. Ponikiewski, “Flexural behaviour of self-compacting concrete reinforced with different types of steel fibres”, Volume 47, Octobre 2013, Pages 397-408 [14] Morteza H. Beigi, Javad Berenjian, Omid Lotfi Omran, Aref Sadeghi Nik, Iman M. Nikbin, “An experimental survey on combined effects of fibres and Nano silica on the mechanical, rheological, and durability properties of self-compacting concrete”, Volume 50, Septembre 2013, Pages 1019-1029 [15] Amin Abrishambaf a, Joaquim A.O. Barros a, Vitor M.C.F. Cunha, “Relation between fibre distribution and post-cracking behaviour in steel fibre reinforced self-compacting concrete panels”, Cement and Concrete Research 51 (2013) 57–66 [16] Shahid Iqbal, Ahsan Alia, Klaus Holschemachera, Thomas A. Bierb, “Effect of change in micro steel fibre content on properties of High strength Steel fibre reinforced Lightweight Self-Compacting Concrete (HSLSCC)”, Procedia Engineering 122 ( 2015 ) 88 – 94 [17] Nan Su, Kung-Chung Hsu, His-Wen Chai, “A simple mix design method for self-compacting concrete”, Volume 31, Issue 12, December 2001, Pages 1799-1807 [18] EFNARC, “Specification and guidelines for self-compacting concrete, English edition”, European Federation for Specialist Construction Chemicals and Concrete systems. Norfolk, UK February 2002. [19] Siddique R., “Properties of self-compacting concrete containing class F fly ash”, Mater Des 2011; 32:1501–7 [20] Felekog lu B, Tosun K, Baradan B, Altun A, Uyulgan B.,”The effect of fly ash and limestone fillers on the viscosity and compressive strength of self-compacting repair mortars”, Cem Concr Res 2006;36:1719–26 [21] Khayat K.H., Guizani Z., “Use of viscosity-modifying admixture to enhance stability of fluid concrete”, ACI Mater J 1997; 94(4); 332-41. [22] H. Fares, S. Remond, A. Noumuwe, A. Cousture, “High temperature behaviour of Self-consolidating concrete microstructure and physicochemical properties”, Cem. Concr. Res. 40 (2010) 488–496.

[414] Mechanical Behavior of Polymer Concrete and Ordinary Cement Concrete Exposed to Elevated Temperatures: A Comparative Study

Brajkishor Prasad1, S. Ganesan2 and Prince Singh3 1Associate Professor, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India 2M.Tech. Student, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India 3Research Scholar, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India E-mail: [email protected]

ABSTRACT In the present study, investigation on mechanical properties of different polymer concretes (PC) with fly ash as filler was conducted and compared with ordinary cement concrete (OCC). The polymer based concretes were also exposed to elevated temperatures and then tested to study the change in mechanical behavior after such an exposure. The mechanical properties i.e. compressive strength, split tensile strength, flexural strength of PC and normal cement concrete were determined. The polymer and fly ash content were kept between 12.4–13.2% and 7.6–9.6% respectively. The results obtained shows that the polymer concrete possess significantly higher mechanical strength as compared to that of normal cement concrete. Also, the polymer and fly ash content need to be controlled properly in order to achieve high strength concretes. The mechanical properties of polymer concrete exposed to elevated temperatures were satisfactory up to 240°C, beyond which it decreased significantly. Keywords: Polymer Concrete, Epoxy Resin, Fly Ash, Elevated Temperature

1. INTRODUCTION Polymer concrete (PC) is a composite material in which fine and coarse aggregates are bounded together with the help of polymer binder. Initially it was used to produce synthetic marbles. The polymer concrete was introduced 1950s. Since 1970s the applications of polymer concrete widespread due to better mechanical properties and durability. Polymer concrete is high performance materials compared to ordinary Portland cement concrete due to its better durability, less curing time, less adhesive properties, resistance to abrasion, freeze and thaw resistance, low permeability to water and aggressive solutions, good chemical and corrosive resistance, can withstand due to payloads, sound and thermal insulation [1–4]. Polymer concrete can be classified into three types (i) Polymer concrete (ii) Polymer cement concrete or Polymer modified concrete (iii) Polymer Impregnated concrete (PIC) (Fowler 1999; Blaga and Beaudion 1985). Generally, Polymer concrete systems consist of polymer resins (binder), fine and coarse aggregates. Polymer concrete has superior mechanical properties than ordinary Portland cement concrete. Mechanical properties of Polymer concrete is based on many factors such as type of polymers, binder dosage, aggregate size distributions, grading of aggregates, type of micro filler, type of fibers, moisture content of aggregates, curing conditions, silane coupling agents, curing temperature and manufacturing process etc [5–7]. The polymer concrete is more costly than conventional concrete so one of the important parameter of polymer concrete was optimization of polymer content which means the least amount of polymer should be used in polymer concrete to achieve better mechanical properties and strength [8]. The selection of polymer resins depends on many factors such as cost effectiveness, strength requirements, easy availability of material sources, environmental effects. Among all polymer resins, epoxy resin gives better mechanical properties and durability than other [9]. Epoxy resin is more costly than other resins. Unsaturated polyester was [415] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) mostly used because it’s low cost, easy availability and better mechanical properties [10]. Polyester resins give same properties to that of epoxy resins by adding micro filler and silane coupling agents [11]. The mechanical properties of polymer concrete increased due to further addition of different type of micro fillers and fibers. Different type of micro filler were used in Polymer concrete, such as fly ash, silica fume, calcium carbonate etc. The main aim of micro filler was to minimize the voids and porosity between the larger and smaller particles resulting in better workability, smooth surface finish, less water absorption, better mechanical properties and durability [12–15]. Fly ash gives better mechanical properties than silica fume [16]. Fly ash increases the compressive strength up to 30% [17]. The types of fibers: steel, glass, carbon, polypropylene, nylon was used in Polymer concrete. The mechanical properties, toughness, fatigue strength, stiffness and excellent resistance of damping increased due to addition of fibers. Polymer concrete has achieved 70–75% of strength in one day. Strength development of Polymer concrete after 7 days is constant. Several researchers investigated the mechanical behavior of PC when exposed to fire and high temperature [18–20] and strength development of PC on different curing temperature, [21–22]. Generally, Polymer resins are flammable but it does not catch fire easily because it contains more mineral aggregates and micro fillers. They concluded that PC has low resistance to fire and high temperatures. The main objectives of this study to do investigation on different factors that influence of characterization of Polymer concrete such as effect of size of aggregates and fly ash, behavior of polymer concrete after incorporation of micro filler and strength variation due to different curing conditions. Strength development of polymer concrete at temperature variations and to study the stress-strain response and variation of modulus of elasticity after exposed to elevated temperature variations.

2. MATERIALS

2.1 Polymer In this study, epoxy (binder) polymer based on BRC-GR 222 was used. It is manufactured from Epichlorohydrine and Bisphenol – A and further modified with reactive diluent. BRC – AH 209 type of hardener was used to cure above epoxy resin at ambient curing (room temperature curing) condition for this study. This type of hardener was used as it has less viscosity so more filler materials can be added. Epoxy resin and hardener were procured from BHARATH RESINS & CHEMICALS based in CHENNAI. The resin and hardener are mixed at a ratio of 2:1 (resin: hardener) to get maximum strength. The physical and mechanical properties of epoxy resin and hardener respectively are presented in table 1 and 2.

Table 1: Physical Property of Epoxy Resin and Hardener Properties BRC–GR 222 BRC–AH 209 Appearance Clear low viscosity liquid Pale yellow liquid Viscosity at 30°C 550–650 cps 300–400 cps Type Room temp. curing Room temp. curing Epoxy equivalent 180–200 – Amine value – 380–420 Specific gravity 1.1–1.2 0.96–0.98 Storage stability 1 year 1 year

Table 2: Mechanical Properties of Epoxy Resin Properties Compressive Tensile Flexural Bond Shrinkage Strength Strength Strength Strength Value (kg/cm2) 600–800 80–110 380–450 65–85 <0.0005cm

[416] Mechanical Behavior of Polymer Concrete and Ordinary Cement Concrete Exposed to Elevated Temperatures:A Comparative Study

2.2 Cement In this paper, comparative study was also made with ordinary cement concrete (OCC). Portland slag cement (PSC) conforming to IS 455:1989 was used to cast ordinary cement concrete. Portland slag cement (PSC) is produce from mixing of Portland slag or Ground Granulated Blast furnace Slag (GGBS) with Portland cement. The maximum quantity of GGBS in PSC 30%. As per IS 4031 physical properties of cement were determined. Chemical and physical properties of Portland slag cement are shown in table 3 & 4.

Table 3: Chemical Properties of Portland Slag Cement

Compound SiO2 Al2O3 Fe2O3 CaO MgO SO3 LOI Content (%) 28.5 10.3 2.93 45.61 3.62 2.63 2.43

Table 4: Physical Properties of Cement

Properties Value Fineness 3% Specific Surface Area 2255 cm2/grams Soundness 1 mm Normal Consistency 33% Initial Setting Time 80 min Final Setting Time 320 min 3 day strength 16.67 N/mm2 Compressive Strength 7 day strength 22.02 N/mm2 28 day strength 33.87 N/mm2

2.3 Aggregates The fine aggregate was procured from locally available KHARKAI river, Jamshedpur with the maximum particle size of 4.75mm. The crushed coarse aggregates were obtained from locally available sources. The coarse aggregate size varies between 4.75mm to 20mm. The physical properties of fine and coarse aggregate are shown in following table 4.

Table 5: Physical Properties of Aggregates Properties Fine Aggregate Coarse Aggregate Particle Size <4.75 mm 65 % (20mm–10mm) & 35 % (10mm–4.75mm) Loose state 1434 kg/m3 1642 kg/m3 Bulk Density Dense state 1663 kg/m3 1840 kg/m3 Packing Factor 1.16 1.12 Water Absorption 0.55 % 0.25 % Specific Gravity 2.63 2.73 Fineness Modulus 2.7 (Zone II) 7.7 Crushing Strength – 13.6 Impact Strength – 7.8

[417] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

2.4 Micro Filler Fly ash is the one of the cheapest building material in construction industry. It is the byproduct of coal. It is one of the cost effective construction material. It improves strength, performance and durability of concrete. Fly ash particle sizes are very small, hence act as filler and helps in reducing the permeability of concrete. Particle size of fly ash < 150µm was used. It was procured from USHA MARTIN PVT. LTD. based at Jamshedpur. Classification of fly ash was class F, which means CaO percentage is less than 7%. The physical and chemical properties of fly ash have been shown in table 5 & 6.

Table 6: Physical Properties of Fly Ash Properties Value Colour Dark grey Loose state 734 kg/m3 Bulk density Dense state 998 kg/m3 Specific gravity 1.98 Fineness 1.4% Water absorption 12.5% Average Particle size 6.92 µm* *Source: Usha Martin Ltd, Jamshedpur.

Table 7: Chemical Composition of Fly Ash (%)

SiO2 Al2O3 Fe2O3 CaO MgO SO3 LOI 55.198 22.62 6.98 8.31 1.056 1.538 2.42 *Source: Usha Martin Ltd, Jamshedpur.

3. PREPARATIONS OF SPECIMENS

3.1 Optimal Dosage of Polymer In the present study, different mix proportions of polymer content were taken. Being a very costly material, polymer needed to be used judicially, hence mix proportions for PC were adopted on the basis of literature studied. It varies from 12.4–16% by the weight of polymer concrete. The different mix proportions of polymer concrete have been shown in table 7. The effect of binder content and fly ash on the properties of concrete was studied. The mechanical properties and thermal behavior of PC and OCC were studied. Different compositions of both Polymer and Ordinary cement concrete are described in table 8.

3.2 Preparation of Polymer Concrete Initially different mix proportions of PC selected as per literature review. The materials used to prepare the PC: epoxy resin (binder) & hardener (in case of epoxy resin), fly ash (micro filler), fine and combined coarse aggregates.

Table 8: Different Mix Proportions of Polymer Concrete Epoxy Resin Fine Aggregate Coarse Aggregate Mixture Filler (%) (%) (0–4.75 mm)(%) 65% (20 – 10mm) 35% (10–4.75mm) M1 12.4 6.4 40.6 40.6 M2 12.4 9.6 37.4 40.6 M3 16.4 7.2 38.2 38.2

[418] Mechanical Behavior of Polymer Concrete and Ordinary Cement Concrete Exposed to Elevated Temperatures:A Comparative Study The different mix proportions of Polymer concrete are presented in table 7. The epoxy resin was thoroughly mixed with hardener in the ratio of 2:1 and kept still to set for 3–5 min. Thereafter, fine & coarse aggregates were mixed thoroughly and along with the fly ash added to get homogeneous mix on adding resin & hardener. The specimens used for PC is 100mm cube for compressive strength, 100mm diameter & 200mm height cylinder for split tensile strength and 100x100x500mm prism for flexural strength. Proper compaction to minimize the voids was done by using vibration table. Specimens were remolded after 24h and cured on room temperature (ambient curing temp. condition) with relative humidity. Three no. of specimens were cast for each test. The specimens were tested on 7 and 28 days of maturity as per IS: 516–1959 [33].

3.3 Preparation of OCC The Portland slag cement was used to prepare the ordinary cement concrete. The following mix proportions 1:1.62:2.91 with W/C ratio of 0.39 was adopted for the preparation of OCC. The mix proportioning of ordinary cement concrete was done on the basis of Indian Standard IS: 10262–2009 and IS:456–2000. The mix composition of OCC has been shown in table 8.

Table 9: Composition of Ordinary Cement Concrete

Materials Cement (kg/m3) Water (kg/m3) Sand (kg/m3) Gravel (kg/m3) Experimental Density (kg/m3) Dosage 415 197 1022 1110 2487 The standard specimens were used for casting of ordinary cement concrete i.e. cube (150 x 150 x 150mm), cylinder (150mm diameter, 300mm height) and prism (100 x 100 x 500mm) as per Indian standard to evaluate compressive strength, split tensile strength and flexural strength respectively.

4. EXPERIMENTAL PROGRAMS

4.1 Mechanical Properties Mechanical properties of polymer and ordinary cement concrete was evaluated by using computer controlled servo hydraulic uniaxial compressive testing machine (capacity-3000kN) with Flexure test frame (capacity-750kN). According to IS 516:1959, the loading rate for compressive & split tensile strength test and flexural strength test were 140 kg/cm2 per min and 7 kg/cm2 per min respectively.

4.2 Exposure to Elevated Temperatures Variations The aim of this study is to investigate mechanical behavior of polymer concrete exposed to high temperatures. The specimens were cured and tested after 28 days of maturity as per IS:516–1959. The different specimens of PC and OCC were kept in rectangular muffle furnace to expose them to different elevated temperatures i.e 40°C, 80°C, 120°C, 160°C, 200°C and 240°C respectively. The specimens kept in muffle furnace were maintained to have a fix rate of heating and cooling of 5°C per minutes. After achieving the required temperature, the specimens were exposed to the temperature for 3 hours and then allowed to cool. Some reference specimens were kept in ambient conditions without heating and cooling. Fig. 1: Rectangular Muffle Furnace [419] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) 5. RESULTS AND DISCUSSION

5.1 Influence of Polymer Content in PC Based on literature review three different mix proportions with different dosages of polymer binder of polymer concrete were taken to study the influence of polymer content in polymer concrete. The composition of different mix proportions of PC are described in table 7. The polymer content varies from 12.4–16% of total weight of polymer concrete. The mechanical properties of different mix proportions of PC were determined. The lower amount of resin content results in poor workability, more porosity and reduced compressive strength. The result show that compressive strength and flexural strength of PC increases directly with the resin content. Further with the increase in the resin content, it achieved the maximum value. After attaining maximum value these either decreased, that particular resin content gives optimum properties, it known as optimum polymer content. The optimum resin content generally varies between 10–16% of total weight of polymer concrete.

100100100 77 days7days days strength strength strength 2828 days days strength strength

8080 80

60 6060

(N/mm2) 40 40(N/mm2) (N/mm2)

strength Compressive 20 strength Compressive 20 strength Compressive

0 0 0 M1M1 M2M2 M3M3 M1 M2 M3 MixMix proportions proportions Mix proportions (a) (a) (a) (a)

7 days strength 28 days strength 7 days7 days strength strength 2828 days days strength strength 7 days strength 28 days strength 12 2525 7 days strength 28 days strength 12 7 days strength 28 days strength 12 25 1010 2020 10 20 8 8 15 15 8 6 6 15 10 10 4 64 10 5 5 2 42

Flexural strength (N/mm2) Flexural 5 0

Flexural strength (N/mm2) Flexural 2 0 (N/mm2) strength tensile split 0 0 (N/mm2) strength tensile split M1 M2 M3 M1M1 M2M2 M3M3 M1 M2 M3 Flexural strength (N/mm2) Flexural 0 0 Mix proportions (N/mm2) strength tensile split MixMix proportions proportions M1 Mix M2proportions M3 M1 M2 M3 (b) Mix(c) proportions(c) (b) Mix (b) proportions (c) Fig. 2: (a) Compressive Strength (b) Flexural Strength (c) Split Tensile Strength of Polymer(c) Concrete FigFig 2 2(a) (a) Compressive Compressive (b) strength strength (b) (b) Flexural Flexural strength strength (c) (c) Split Split tensile tensile strength strength of of Polymer Polymer concrete concrete Fig 2 (a) Compressive strength (b) Flexural strength (c) Split tensile strength of Polymer concrete 5.35.3 Exposure Exposure to to elevated elevated temperatures temperatures TheThe mechanical mechanical properties properties (compressive (compressive strength, strength, split split tensile tensile strength, strength, flexural flexural strength), strength), stress stress- - 5.3 Exposure to elevated temperatures [420] strainstrain behavior behavior were were determined. determined. The The temperature temperature variations variations selected selected based based on on literature literature review. review. TheThTh emechanical especimens specimens wereproperties were stable stable (compressive up up to to 24 240 0̊C. ̊C. Whenstrength, When the the splittemperatur temperatur tensilees esstrength, exceeds exceeds 24flexural 240 0̊C, ̊C, the thestrength), degradation degradation stress - strain behavior were determined. The temperature variations selected based on literature review. isis started. started. When When the the specimens specimens are are e xposedexposed to to high high temperatures temperatures (>24 (>240 0̊C), ̊C), debonding debonding starts starts Thbetweenebetween specimens aggregate aggregate were and stableand binder, binder, up to it 24itgenerates generates0 ̊C. When the the thecracks. cracks. temperatur The The pore porees exceedssize size diameter diameter 240 ̊C, also alsothe increased degradationincreased when the temperature increased. Fig 3 and 4 both shows that variation of mechanical strength is started.when the When temperature the specimens increased. are Fig e xposed3 and 4 toboth high shows temperatures that variation (>24 of0 mechanical̊C), debonding strength starts with temperatures variations. It observed that compressive strength of PC reduces when betweenwith temperaturesaggregate and variations. binder, itIt generatesobserved thethat cracks. compressive The pore strength size diameterof PC reduces also increased when temperatures increased. From the fig 5(c) the flexural strength of PC enhanced, due to whentemperatures the temperature increased. increased. From Figthe 3fig and 5(c) 4 boththe flexuralshows thatstrength variation of PCof mechanicalenhanced, duestrength to temperatures rises up to 160 ̊C after that flexural strength reduced when the temperatures withtemperatures temperatures rises variations. up to 160 It̊C observedafter that thatflexural compressive strength reducedstrength when of PCthe reducestemperatures when increased. The mass loss varies 0.12-0.9%. When the temperature increasing all PC specimens temperaturesincreased. Theincreased. mass loss From varies the 0.12 fig-0.9%. 5(c) Whenthe flexuralthe temperature strength increasing of PC allenhanced, PC specimens due to were breaks in a brittle manner. temperatureswere breaks rises in a brittleup to manner. 160 ̊C after that flexural strength reduced when the temperatures increased. The mass loss varies 0.12-0.9%. When the temperature increasing all PC specimens were breaks in a brittle manner.

Mechanical Behavior of Polymer Concrete and Ordinary Cement Concrete Exposed to Elevated Temperatures:A Comparative Study

5.2 Exposure to Elevated Temperatures The mechanical properties (compressive strength, split tensile strength, flexural strength), stress-strain behavior were determined. The temperature variations selected based on literature review. The specimens were stable up to 240°C. When the temperatures exceeds 240°C, the degradation is started. When the specimens are exposed to high temperatures (>240°C), debonding starts between aggregate and binder, it generates the cracks. The pore size diameter also increased when the temperature increased. Fig 3 and 4 both shows that variation of mechanical strength with temperatures variations. It observed that compressive strength of PC reduces when temperatures increased. From the fig 5(c) the flexural strength of PC enhanced, due to temperatures rises up to 160°C after that flexural strength reduced when the temperatures increased. The mass loss varies 0.12–0.9%. When the temperature increasing all PC specimens were breaks in a brittle manner. 5.4 Comparison between OCC and PC The 5.3residual Co mpmechanicalarison bet propertiesween OCC of andPC comparedPC to OCC on exposure at elevated temperature variations.The residual The ordinary mechanical cement properties concrete of PC were compared cast and to testedOCC onas wellexposure as polymer at elevated concrete. temperature The OCCvariations. specimens The wereordinary expose cementd concreteto same were thermal cast and treatments tested as wellas aswell polymer as PC. concrete. The Theresidual OCC mechanicalspecimens properties were exposed of polymerto same thermalconcrete treatments (PC) and as wellOrdinary as PC. Thecement residual concrete mechanical (OCC) properties were calculatedof polymer after concrete exposure (PC) to andhigh Ordinary temperatures cement variations.concrete (OCC) The wereweight calculated loss of afterPC andexposure OCC to with high temperaturetemperatures is shown variations. in fig The 6. weight loss of PC and OCC with temperature is shown in fig 6.

100 OCC PC 80

40 (N/mm2) (N/mm2) 20 strength Compressive Compressive strength Compressive 0 27 40 80 120 160 200 240 Temperature ( ̊C)

Fig.Fig 3: 3 ResidualResidual Compressivecompressive strengthStrength

14 12 OCC comp 12 10 8 6 (N/mm2) (N/mm2) 4 Split tensile strength tensile Split strength tensile Split 2 0 27 40 80 120 160 200 240 Temperature ( ̊C)

Fig 4 ResidualFig. 4: Residualsplit tensile Split strength Tensile Strength

OCC[421] PC 30

10 5 Flexural strength (N/mm2) Flexural Flexural strength (N/mm2) Flexural 0 27 40 80 120 160 200 240 Temperature ( ̊C)

5.4 Comparison between OCC and PC The residual mechanical properties of PC compared to OCC on exposure at elevated temperature variations. The ordinary cement concrete were cast and tested as well as polymer concrete. The OCC specimens were exposed to same thermal treatments as well as PC. The residual mechanical properties of polymer concrete (PC) and Ordinary cement concrete (OCC) were calculated after exposure to high temperatures variations. The weight loss of PC and OCC with temperature is shown in fig 6.

100 OCC PC 80

40 (N/mm2) 20 Compressive strength Compressive 0 27 40 80 120 160 200 240 Temperature ( ̊C)

Fig 3 Residual compressive strength

14 OCC comp 12 10 8 6 (N/mm2) 4

strength tensile Split 2 0 27 40 80 120 160 200 240 Temperature ( ̊C)

e-Book: 2nd NationalFig 4 Residual Conference split on Recent tensile Advances strength in Civil Engineering (RACE-II)

OCC PC 30

10 5

Flexural strength (N/mm2) Flexural 0 27 40 80 120 160 200 240 Temperature ( ̊C) Fig. 5: Residual Flexural Strength Fig 5 Residual flexural strength

4 3.5

3 PC OCC 2.5 2 1.5

Weight loss Weight loss (%) 1 0.5 0 27 40 80 120 140 160 200 240 Temperature ( ̊C)

Fig. 6: Weight Loss for Specimens Exposed to Elevated Temperatures It was observedFig 6that Weight the least loss mass for specimensloss occurs exposedin PC comparison to elevated to OCC.temperatures When the specimens were exposed to higher temperature, it leads to high mass losses for both PC and OCC. Thermal degradation It wasin OCCobserved is more that predominates the least mass than loss that occurs of PC samples.in PC comparison When the increasing to OCC. temperatureWhen the specimensis more than were160°C exposed it releases to higher the smokes. temperature, The residual it leads compressive to high mass strength losses variation for both versus PC temperature and OCC. variationsThermal is degradationshown in infig 3.OCC It reveals is more that polymerpredominates concrete thanpossess that more of strengthPC samples. than ordinary When cement the increasing concrete up temperatureto 200°C. isIt wasmore observed than 160 that ̊Cthe it residual releases compressive the smokes. strength The variation residual of compressiveOCC remains unchangedstrength variationup to versus240°C. temperatureFor PC, it is observedvariations that is shownthe compressive in fig 3. Itstrength reveals decrease that polymer when temperatureconcrete possess exceeds 160°C. At 240°C both PC and OCC Possess almost similar residual compressive strength. Fig 5 shows moreflexural strength strength than variation ordinary with cement respect concrete to temperature. up to 200It changes ̊C. It foundwas observedthat the flexural that thestrength residual of PC compressiveincrease withstrength increase variation in temperature of OCC upremains to 160°C unchanged after that updecreased to 240 ̊C.with For increasing PC, it istemperatures. observed that Howeverthe compressive the obtained strength residual decre flexuralase when strength temperature of PC is more exceeds compared 160 ̊C. to At OCC 240 even ̊C both at 240°C PC and too. OCCPolymer Possess concrete almost has similar better mechanical residual propertiescompressive when strength. exposed toFig temperature 5 shows up flexural to 240°C. strength when the variationtemperature with respect exceeds to 240°C temperature. the degradation It changes starts, foundresulting that in lossthe offlexural mechanical strength and physicalof PC increase properties withof increa polymerse inconcrete. temperature It is recommended up to 160 ̊Cthat after polymer that concretedecreased is notwith suitable increasing when temperatures.exposed to high temperatures (more than 240°C) However the obtained residual flexural strength of PC is more compared to OCC even at 240 ̊C too. Polymer concrete has better mechanical properties when exposed to temperature up to 240 ̊ C. when the temperature exceeds 240 ̊C the degradation starts, resulting in loss of mechanical and physical properties of polymer concrete. It [is422 recommended] that polymer concrete is not suitable when exposed to high temperatures (more than 240 ̊C) 6. Conclusion and recommendations

 The optimization of the mechanical properties of PC depends on many factors such as grading of aggregates, type of resin used for PC, sizes of fly ash. Mechanical properties, modulus of elasticity, thermal tests show that optimal polymer content is 12.4% which leads to achieve the better physical and mechanical properties at lower cost.  The optimum polymer content PC to that of OCC was exposed to temperatures at the intervals of 40 ̊C. The PC specimens were exposed to maximum high temperature up to 240 ̊C for 3h. The selection of temperatures based on thermal properties of resins. The residual mechanical properties of PC specimens observed on exposure to high temperatures for 3h. It is concluded that strength variations observed when temperatures below 160 ̊C which is residual compressive and flexural strength of PC increased with increasing temperature up to 160 ̊C and temperatures exceeds 160 ̊C PC specimens starts Mechanical Behavior of Polymer Concrete and Ordinary Cement Concrete Exposed to Elevated Temperatures:A Comparative Study 6. CONCLUSION AND RECOMMENDATIONS ●● The optimization of the mechanical properties of PC depends on many factors such as grading of aggregates, type of resin used for PC, sizes of fly ash. Mechanical properties, modulus of elasticity, thermal tests show that optimal polymer content is 12.4% which leads to achieve the better physical and mechanical properties at lower cost. ●● The optimum polymer content PC to that of OCC was exposed to temperatures at the intervals of 40°C. The PC specimens were exposed to maximum high temperature up to 240°C for 3h. The selection of temperatures based on thermal properties of resins. The residual mechanical properties of PC specimens observed on exposure to high temperatures for 3h. It is concluded that strength variations observed when temperatures below 160°C which is residual compressive and flexural strength of PC increased with increasing temperature up to 160°C and temperatures exceeds 160°C PC specimens starts reduction in residual properties due to thermo-oxidative degradation of epoxy resin and it’s debonding between epoxy resin to aggregates. So it is recommended that polymer concrete are not suitable when exposed to high temperatures (>160°C). ●● Ordinary cement concrete (OCC) prepared by using same aggregates and coarse to fine aggregates ratio. It possess low mechanical properties compared to PC. PC specimens are more efficient than that of OCC when the temperature rises up to 240°C.

REFERENCES [1] Hisham Abdel-Fattah U, Moetaz M. El-Hawary, Flexural behavior of polymer concrete. Construction and Building Materials 13-1999.253]262. [2] M.C.S. Ribeiro, C.M.L. Tavares and A.J.M. Ferreira. Chemical resistance of epoxy and Polyester Polymer Concrete to acids and salts. [3] Andrzej Garbacz, Joanna J. Sokołowska. Concrete-like polymer composites with fly ashes Comparative study. Construction and Building Materials 38 (2013) 689–699. [4] Jane Proszek Gorninskia,*, Denise C. Dal Molinb, Claudio S. Kazmierczaka. Study of the modulus of elasticity of polymer concrete compounds and comparative assessment of polymer concrete and portland cement concrete. Cement and Concrete Research 34 (2004) 2091–2095. [5] Raman Bedi, Rakesh Chandra, and S. P. Singh. Mechanical Properties of Polymer Concrete. Hindawi Publishing Corporation, Journal of Composites Volume 2013, Article ID 948745, 12 pages http://dx.doi.org/10.1155/2013/948745. [6] Sang-Hoon Hyun, Jung Heum Yeon, Strength development characteristics of UP-MMA based polymer concrete with different curing temperature. Construction and Building Materials 37 (2012) 387–39.7 [7] Header Haddad, Mohammad Al Kobaisi. Influence of moisture content on the thermal and mechanical properties and curing behavior of polymeric matrix and polymer concrete composite. Materials and Design 49 (2013) 850–856. [8] C. Vipulanandan Associate Member, ASCE and E. Paul, Characterization of Polyester Polymer and Polymer concrete. Civil Engg materials 1993:5(1):68-82. [9] P. Mani, A.K. Gupta and S. Krishnamoorthy. Comparative study of epoxy and polyester resin-based polymer concretes. [10] Joao Marciano Laredo dos Reis Mechanical characterization of fiber reinforced Polymer Concrete. Materials Research, Vol. 8, No. 3, 357-360, 2005. [11] R. D. Maksimov, L. Jirgens, J. Jansons, and E. Plume. Mechanical properties of polyester polymer-concrete. Mechanics of Composite Materials, Vol. 35, No. 2, 1999 [12] C. Atzeni, L. Massidda & U. Sanna, Mechanical Properties of Epoxy Mortars with Fly Ash as Filler. Cement & Concrete Composites 12 (1990) 3-8. [13] M. Golestaneh. Amini, .D. Najafpour and A. Beygi. Evaluation of Mechanical Strength of Epoxy Polymer Concrete with Silica Powder as FillerWorld Applied Sciences Journal 9 (2): 216-220, 2010. ISSN 1818-4952 © IDOSI Publications, 2010. [14] Weena Lokuge, Thiru Aravinthan. Effect of fly ash on the behaviour of polymer concrete with different types of resin. Materials and Design 51 (2013) 175–181. [15] K. T. Varughese & B.K Chaturvedi, Fly ash as fine aggregate in Polyester based Polymer Concrete. Cement & Concrete composites 18 (1996), 105-108.

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[16] Marinela Barbu°a; Maria Harja; and Irina Baran. Comparison of Mechanical Properties for Polymer Concrete with Different Types of Filler. J Mater Civ Eng 2010;22(7): 696–701. [17] Y. Ohama and K. Demura. Relation between curing conditions and compressive strength of polyester resin concrete. [18] Elalaoui Oussama, Ghorbel Elhem, Mignot Valérie, Ben Ouezdou Mongi. Mechanical and physical properties of epoxy polymer concrete after exposure to temperatures up to 250°C. Construction and Building Materials 27 (2012) 415–424 [19] Moetaz M. El-Hawarya,U, Hisham Abdel-Fattahb. Temperature effect on the mechanical behavior of resin concrete. Construction and Building Materials 14-2000.317]323. [20] Tumadhir M, Al-Jabiri, Resistance of Polymer Concrete to high temperature. Journal of Babylon Universit/ Engineering sciences No.2, Vol. 21, 2013. [21] Sang-Hoon Hyun, Jung Heum Yeon, Strength development characteristics of UP-MMA based polymer concrete with different curing temperature. Construction and Building Materials 37 (2012) 387–39.7 [22] M.C.S Ribeiro, P.R. Novoa, A.J.M Ferreira, A.T Marques, Flexural performance of polyester and epoxy polymer mortars under severe thermal conditions. Cement & Concrete Composites 26(2004), 803-809.

[424] Cu(II) and Pb(II) Uptake by Granular Activated Alumina Columns Exposed to Mono–and Binary–Metal Ion Systems under a Fixed Concentration Gradient

Manoj Kumar Yadav1 and Mohammad Jawed2 1Research Scholar, Department of Civil Engineering, Indian Institute of Technology, Guwahati, India 2Professor, Department of Civil Engineering, Indian Institute of Technology, Guwahati, India E-mail: [email protected]

ABSTRACT Adsorption is one of the most widely applied techniques for environmental remediation of toxic heavy metals. In this study, the uptake potential of granular activated alumina (GAA) is evaluated in a fixed column bed under uncontrolled pH conditions but with a fixed concentration gradient from mono– and binary–metal ion systems with a fixed total initial metal concentration of 0.60 meq/L. When the exhausted bed with a mono–metal ion system exposed to another mono–metal ion system, displacement of adsorbed metal ion from the bed is observed. When exhausted bed with combination–I of binary–metal ion system exposed to combination–II of binary–metal ion system, displacement of Cu(II) is observed. However, when exhausted bed with combination–II of binary–metal ion system exposed to combination–I of binary–metal ion system, displacement of neither Pb(II) nor Cu(II) is observed. The results of column studies with mono–metal ion systems indicates that the metal uptake by virgin bed is higher for Cu(II) than Pb(II) and in binary–metal ion systems, the metal uptake by virgin bed is higher for combination–I of binary metal ion system than combination–II of binary metal ion system. Keywords: Adsorption, Activated Alumina, Column Studies, Cu(II), Pb(II), Mono–Metal, Binary–Metal

1. INTRODUCTION The presence of heavy metals in water and wastewater even at low concentrations cause adverse effects on health, environmental toxicity and the aesthetic quality of the water environment (Aklil et al., 2004), therefore, heavy metal ions needed to be removed at the source in order to avoid pollution of natural waters and subsequent metal accumulation in the food chain. Effluent from smelting, electroplating, drug manufacturing, paint preparation, alloy manufacture, galvanizing operations, printing, dyeing, paper making, ceramics manufacture and inorganic dyestuff preparation are the major sources of heavy metals (Liu et al., 2008). Methods such as, precipitation, cementation, sedimentation, filtration, coagulation, flotation, complexing, solvent extraction, membrane separation, electrochemical technique, biological process, reverse osmosis, ion exchange and adsorption can be used for the removal of heavy metals from aqueous phase (Gupta et al., 2003). However, the method of adsorption has been found to be superior to other techniques because of its capability of adsorbing a broad range of different heavy metals efficiently as well as simplicity in the process design (Ahmad et al., 2007). In the past, a large number of studies have been conducted on the removal of heavy metal from mono– metal ion systems using different types of adsorbents (Febrianto et al., 2009; Gupta et al., 2001; Karimi et al., 2012). Most of these works have tried to evaluate the uptake capacity of adsorbent for the removal of single metal ion from the aqueous phase by carrying out experiments at particular experimental condition related with effect of pH, agitation/mixing, dose of adsorbent, initial concentration of adsorbate, variation in temperature, kinetic etc. in batch mode and continuous mode column breakthrough studies (Öztürk & Kavak, 2005). The batch mode studies are usually limited to the treatment of small quantities of water or wastewater. Moreover, batch operations are very easy to apply in the laboratory study, but less convenient for field applications. The sorption capacity of the sorbent, obtained from batch equilibrium experiment, is [425] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) useful in providing fundamental information about the effectiveness of sorbate–sorbent system. However, the data obtained under batch conditions are generally not applicable to most treatment system (such as column operations) where contact time is not sufficiently long for the attainment of equilibrium. Thus, it is necessary to ascertain the practical applicability of the sorbent in the continuous mode (Dwivedi et al., 2008). The competitive adsorption of Pb(II) and Cu(II) on chaff in a fixed bed column was studied by Han et al. (2006). Chaff was packed into a glass column (1.5 cm in diameter and 30 cm in height). The mass of chaff in the column was 4.24 g. The metal solution containing Pb(II) or Cu(II) or Pb(II) + Cu(II) both were applied to the column. The pH of metal solution was adjusted to 5 and was not controlled during the process. The metal solution was pumped to the column in a down–flow direction at a rate of 7.5 mL/min. To investigate the effect of coexistence ions on the adsorption of chaff, column studies were performed in three sets (a) the column of chaff was saturated by Cu(II) solution of 9.97 mg/L, then Pb(II) solution of 32.5 mg/L, equal mol–concentration with Cu(II) solution, was passed through the column, (b) column of chaff was saturated by Pb(II) of 24.4 mg/L, then the Cu(II) solution of 7.49 mg/L, equal mol–concentration with Pb(II) solution, was passed through the column, and (c) Cu(II) and Pb(II) adsorbed synchronously by chaff with the metal ions concentration of Cu(II) and Pb(II) were 14.7 mg/L and 50.6 mg/L, respectively. The result of the first two sets of experiment, when the exhausted column with one metal ion system was again exposed with the second metal ion system, there was displacement of already adsorbed metal ion from the surface of chaff. The result of the third set indicated that the mechanism of the two metal ions was in homology nearly. The tendency for adsorbed Pb(II) was higher than that for Cu(II). These experiments were performed on mole basis and concentration gradient in single–metal ion system was different from the binary–metal ion systems, therefore, difficult to appreciate the results fully. The past studies have not assessed and analyzed further adsorption potential of metal ion onto metal loaded adsorbent when exposed to another metal and subsequent displacement of already adsorbed metal ion. Hence, the objective of the study is to develop and analyze breakthrough curves with a mono– or a combination of binary–metal ion system of Cu(II) and Pb(II) followed by reloading of exhausted bed with another mono– or another combination of binary–metal ion system under uncontrolled pH conditions but with a fixed concentration gradient.

2. MATERIALS AND METHODS

2.1 Materials The commercial grade granular activated alumina (GAA) used in this study was procured from M/S Siddhartha Industries, Surat (India) and its physical and chemical properties are presented in Table 1. For the present study, copper [Cu(II)] and lead [Pb(II)] metal ions have been selected and its characteristics are presented in Table 2. The criteria used for the selection of the metal ions are similar valence of the two metals but with different atomic weights.

Table 1: Properties of Granular Activated Alumina Characteristics Value Particle form Granular Particle size (mm) 0.40–1.20 Surface area (m2/g) (minimum) 360 Physical Pore volume (cc/g) 0.50 Packed bulk density (g/cm3) 0.72 Bed crushing strength (wt. %) (minimum) 99.2–99.9 Loss on abrasion (wt. %) (maximum) 0.50

Table 1 (Contd.)... [426] Cu(II) and Pb(II) Uptake by Granular Activated Alumina Columns Exposed to Mono–and Binary–Metal Ion Systems

...Table 1 (Contd.)

Characteristics Value

Al2O3 (%) 92.50

Chemical SiO2 (%) 0.025

Na2O (%) 0.30 Source: M/S Siddhartha Industries, Surat, India

Table 2: Characteristics of the Selected Heavy Metals Ionic Radiusb Metal Ion Charge Atomic Weighta (g) Electronegativityc (Ao) Copper +2 63.55 0.72 1.90 Lead +2 207.19 1.20 1.87 a Sawyer et al. (2003), b Hawari & Mulligan (2007), c Pauling (1960)

2.2 Methods The stock solution of Cu(II) and Pb(II) metal ion of 1000 mg/L concentration were prepared by dissolving known amounts of analytical grade copper sulfate [Cu(SO4). 5H2O)] and lead nitrate [Pb(NO3)2] respectively in de–mineralized water (electrical conductivity = 0.002±001 mmho/cm, total hardness =

2.0±0.2 mg/L as CaCO3, pH = 6.6±0.3) prepared through RO process (Model: Milli–Q Water, M/S Millipore S.A.S., Molsheim, France). The working metal solutions for Cu(II) and Pb(II) ions were prepared by diluting the respective stock solution. The initial pH of working metal solutions was adjusted to 5 using appropriate strengths of acid (HCl) or base (NaOH) and solution pH was not checked or controlled during the experiment–hence termed as uncontrolled pH conditions. The residual concentrations of Cu(II) and Pb(II) metal ions were estimated using atomic absorption spectroscopy (Model: 55 B, M/S Spectra AA Varian, Australia).

2.3 Column Studies Column experiments were conducted using a glass tube of 2 cm inner diameter. A schematic of the experimental setup used is shown in Fig. 1. A perforated (openings < 1 mm) circular metal plate was fixed at the bottom of the glass tube. A thin layer (approximately 2 mm in thickness) of glass wool was placed over the metal plate to prevent loss of GAA through perforated openings. 9.40 g GAA was packed into the column with gentle jerks giving a bed depth of 3.0 cm. In this study, the initial concentrations of 0.60 meq/L of Cu(II) and Pb(II) metal ions were used in mono–metal ion systems. The working solutions in the case of binary–metal ion systems were prepared in two different combinations: combination–I comprised of Cu(II) = 0.45 meq/L + Pb(II) = 0.15 meq/L and combination–II comprised of Cu(II) = 0.15 meq/L + Pb(II) = 0.45 meq/L. The working metal solution was prepared in required volume and its initial pH was adjusted to 5 using appropriate strength of HCl or NaOH solution. The prepared working metal solution was fed to the GAA bed column in up flow mode using a peristaltic pump (Model: PP20 EX–2C, M/S Miclins, India) at a constant flow rate of 1.0 mL/min. The virgin bed of the column was initially exhausted with the working solution of any one of the mono–metal ions or a combination of binary–metal ions. The exhausted bed was washed with approximately 20 bed volumes using de–mineralized water in downflow mode to remove any of the un–adsorbed metal ions remaining in the pore volumes of the bed. The washed exhausted bed was then reloaded with the working solution of the second mono–metal ion or the second combination of the binary–metal ions. Samples were collected from the effluent at regular intervals and concentrations of the metal ions present were analyzed. All the column studies were conducted in duplicate and average values were used in the analysis of the experimental data. [427]

Miclins, India) at a constant flow rate of 1.0 mL/min. The virgin bed of the column was initially exhausted with the working solution of any one of the mono–metal ions or a combination of binary–metal ions. The exhausted bed was washed with approximately 20 bed volumes using de–mineralized water in downflow mode to remove any of the un–adsorbed metal ions remaining in the pore volumes of the bed. The washed exhausted bed was then reloaded with the working solution of the second mono–metal ion or the second combination of the binary–metal ions. Samples were collected from the effluent at regular intervals and concentrations of the metal ions present were analyzed. All the column studies were conducted in duplicatee-Book: 2 ndand National average Conference values on wereRecent used Advances in the in Civil analysis Engineering of the (RACE-II) experimental data.

2 cm dia

Effluent

Activated alumina Glass wool bed = 3 Influent cm Storage Perforated mesh Air vent Sample Collection

Peristaltic pump

Fig.Fig. 1: 1: Schematic Schematic of of experimentalExperimental setSet-up–up Usedused inin Columncolumn Study study.

3. RESULTSRESULTS ANDAND DISCUSSION DISCUSSION

A series of columnA series studies of column were studies carried were out tocarried understand out to understandthe behavior the of behavior GAA for of uptake GAA offor Cu(II) and uptakePb(II) ions of fromCu(II) mono– and andPb(II) binary–metal ions from ion mono systems– and under binary uncontrolled–metal ion pH conditionssystems under but with a fixeduncontrolled concentration pH gradient. condition Further,s but with studies a fixed were concentration also carried outgradient to examine. Further, the studies potential were of exhaustedalso bed withcarried a mono–metal out to examine or athe combination potential of of exhausted binary–metal bed withsystem a mono for retention–metal or of a othercombination mono–metal of or anotherbinary combination–metal system of binary–metal for retention system of other and/or mono displacement–metal or anotherof previously combination adsorbed of metal binary ion(s).– metal system and/or displacement of previously adsorbed metal ion(s). 3.1 Breakthrough Curves for Virgin GAA Bed Exhausted with Cu(II) Ion and Washed BreakthroughExhausted Bcurvesed R eloadedfor virgin w GAAith P bedb(II exhausted) Ion with Cu(II) ion and washed exhausted bed reloaded with Pb(II) ion The typical breakthrough curves in terms of metal ion remaining in effluent (Ct) versus time for virgin GAA bed loadedThe twithypical working breakthrough solution curvesof Cu(II) in metal terms ion of (initial metal concentration ion remaining = 0.60in effluent meq/L) (C followedt) by reloadingversus time of washed for virgin exhausted GAA bedbed loadedwith working with working solution solutionof Pb(II) ofmetal Cu(II) ion (initialmetal ionconcentration (initial = 0.60 concentratmeq/L) is presentedion = 0.60 in meq/L) Fig. 2. Thefollowed breakthrough by reloading curve of of washedthe bed exhaustedwhen loaded bed with with working working solution of mono–metalsolution of Cu(II)Pb(II) ionmetal increased ion (initial very concentratslowly in theion initial= 0.60 phase meq/L) of theis presented operation in i.e. Fig. up 2to. The200 min. Afterbreakthrough initial 200 min., curve it increasedof the bed at when a faster loaded rate withand workingreached asolution value ofof 0.473mono –meq/Lmetal atCu(II) 3270 ion min. of operation.increased After ver 3270y slowly min., in the the breakthrough initial phase ofcurve the increasedoperation i.e.very up slowly to 200 and min. the After bed appearedinitial 200 to get exhaustedmin., atit increased4000 min. atof aoperation faster rate (Fig. and 2). reachedWhen the a bedvalue exhausted of 0.473 with meq/L Cu(II) at ion3270 was min. washed of and then operation.reloaded with After Pb(II) 3270 ion min.,solution, the itbreakthrough yielded a relatively curve steeper increased breakthrough very slowly curve and compared the bed to the breakthroughappeared curveto get ofexhausted the virgin at bed. 4000 The min. effluent of operation concentration (Fig. 2 became). When constantthe bed atexhausted around 2250with min. of operation indicating saturation of the bed (Fig. 2). Along with the adsorption of Pb(II) ion on GAA when the exhausted bed was reloaded with Pb(II) ion solution, displacement of adsorbed Cu(II) ion from the bed took place. Initially the displacement of adsorbed Cu(II) from the bed increased rapidly and then decreased gradually after peaking at 250 min. (Fig. 2). It is also observed that during the initial phase i.e. first 250 min. of operation, when the displacement of Cu(II) ion took place at very high rate, the Pb(II) ion was not detected in the effluent. It meant complete removal of Pb(II) took place in the initial phase of the operation. After 250 min. of operation, displaced Cu(II) ion concentration decreased at faster rate and at

[428] Cu(II) and Pb(II) Uptake by Granular Activated Alumina Columns Exposed to Mono–and Binary–Metal Ion Systems the same time Pb(II) ion concentration in the effluent increased at faster rate. Significant displacement of Cu(II) was observed up to 2250 min. of bed operation. As the displacement of Cu(II) reduced after 2250 min. of operation, the effluent Pb(II) concentration from the washed exhausted bed became constant coinciding with the saturation of the bed for Pb(II) retention.

Fig. 2: Breakthrough Curves for Virgin GAA Bed Exhausted with Cu(II) Metal Ion and Washed Exhausted Bed Reloaded with Pb(II) Metal Ion [Initial Cu(II) conc. = 0.61±0.01 meq/L, Initial Pb(II) conc. = 0.60±0.00 meq/L; Initial Adjusted pH = 4.9±0.1; Effluent pH = 5.6±0.5; Temp. = 30±1 oC] The amount of metal retained in the virgin and washed exhausted bed was estimated by calculating the area above the breakthrough curve up to the initial concentration of the metal ion being loaded on the bed using the trapezoidal rule (Cardoso et al., 2011). The amount of metal ions which came out of the bed during washings was also estimated. The amount of metal displaced by the washed exhausted bed was estimated by calculating the area below the curve using the trapezoidal rule. Mass balance of metal retained in the bed from mono–metal ion systems was carried out for a time period when effluent metal concentration was less or equal to 60% of the influent metal ion concentration for both virgin bed loading and exhausted bed reloading. In the case of the virgin bed loaded with Cu(II) ion solution, exhaustion time

(tE) came out as 2361 min. with metal retention of 1.020 meq. Total amount of un–absorbed metal ion in the washing was estimated as 0.003 meq. After washing, the exhausted bed was reloaded with Pb(II) solution, the uptake of Pb(II) on the bed after 973 min. of exhaustion time was estimated as 0.439 meq and 0.394 meq of Cu(II) was displaced from the bed. Hence the total uptake of the bed was estimated as 1.062 meq and the total metal uptake per unit weight of the adsorbent was estimated as 0.113 meq/g.

[429] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

3.2 Breakthrough Curves for Virgin GAA Bed Exhausted with Pb(II) Ion and Washed Exhausted Bed Reloaded with Cu(II) Ion The typical breakthrough curves for virgin GAA bed loaded with working solution of Pb(II) metal ion (initial concentration = 0.60 meq/L) followed by reloading of washed exhausted bed with working solution of Cu(II) metal ion (initial concentration = 0.60 meq/L) is presented in Fig. 3. The breakthrough curve of the bed when loaded with working solution of mono–metal Pb(II) ion increased very slowly in the initial phase of the operation i.e. up to 150 min. After initial 150 min., it rapidly increased and reached a value of 0.473 meq/L at 1250 min. of operation. After 1250 min., the breakthrough curve increased very slowly and the bed appeared to get exhausted at 1500 min. of operation (Fig. 3). When the bed exhausted with Pb(II) ion was washed and then reloaded with Cu(II) ion solution, it yielded a relatively steeper breakthrough curve compared to the breakthrough curve of the virgin bed up to initial 75 min (Fig. 3). After initial 75 min. of operation, the breakthrough curve decreased slowly and reached to a minimum level of 0.15 meq/L around 1250 min. After 1250 min., it started to rise again and got saturated around 3000 min. of operation. During the reloading of exhausted bed with Cu(II) ion solution, displacement of adsorbed Pb(II) ion took place. Initially the displacement of adsorbed Pb(II) from the bed increased rapidly and then decreased gradually after peaking at 50 min. of operation.

Fig. 3: Breakthrough Curves for Virgin GAA Bed Exhausted with Pb(II) Metal Ion and Washed Exhausted Bed Reloaded with Cu(II) Metal Ion [Initial Pb(II) Conc. = 0.60±0.02 meq/L, Initial Cu(II) Conc. = 0.60±0.02 meq/L; Initial Adjusted pH = 4.9±0.0; Effluent pH = 5.6±0.6; Temp. = 30±1 oC] Mass balance of metal retained in the bed from mono–metal ion systems was carried out for a time period when the effluent metal concentration was less than or equal to 70% of influent metal concentration for

[430] Cu(II) and Pb(II) Uptake by Granular Activated Alumina Columns Exposed to Mono–and Binary–Metal Ion Systems the virgin bed loading and for washed exhausted bed reloading. In the case of the virgin bed loaded with

Pb(II) ion solution, exhaustion time (tE) came out to be 717 min. As Cu(II) breakthrough curve did not reached 70% concentration of influent, hence for the purpose of carrying out mass balance for metal retained, the breakthrough curve for Cu(II) was considered up to the exhaustion time for Pb(II) exhaustion i.e. 717 min. The metal retained in fresh bed after 717 min. was estimated as 0.315 meq. The exhausted bed was washed with 20 bed volumes of de–mineralized water to remove un–adsorbed metal ions from pore volumes of the bed. Total amount of un–absorbed metal ion in the washing was estimated as 0.020 meq. After washing, the exhausted bed was reloaded with Cu(II) solution, the uptake of Cu(II) on the bed up to 717 min. was estimated as 0.310 meq and 0.094 meq of Pb(II) was displaced from the bed. Hence the total uptake of the bed was estimated as 0.512 meq and the total metal uptake per unit weight of the adsorbent was estimated as 0.054 meq/g. The virgin bed when loaded with working solution of mono–metal Pb(II) ion exhausted faster than the virgin bed of same depth when loaded with working solution of mono–metal Cu(II) at the same flow rate. The virgin bed got exhausted approximately at 4000 min. of operation when loaded with Cu(II) metal ion working solution (Fig. 2) but it got exhausted in approximately 1500 min. of operation when loaded with Pb(II) metal ion working solution (Fig. 3). The lower ionic radius and higher electronegativity values of Cu(II) might have facilitated transport through pore openings and adsorption in pore volumes of the adsorbent leading to longer operation of the virgin bed before exhaustion. Whereas larger ionic radius and lower electronegativity values of Pb(II) might have prevented its transport through pore openings and its further restricted movements inside the pore volumes of the adsorbent with lower adsorption levels.

3.3 Breakthrough Curves for Virgin GAA Bed Exhausted with Combination–I of Binary–Metal System and Reloaded with Combination–II of Binary–Metal System The column studies have been performed by loading virgin bed with the working solution of a combination–I of binary–metal ions [0.45 meq/L of Cu(II) + 0.15 meq/L of Pb(II)] having total initial metal ion concentration of 0.60 meq/L till the bed was exhausted or yielded effluents with more than 80% of total initial metal ion concentration. The exhausted bed was then washed with 20 bed volumes of de–mineralized water to remove un–adsorbed metal ions from pore volumes of the bed. The washed exhausted bed was then reloaded with the working solution of the combination–II of binary–metal ions [0.15 meq/L of Cu(II) + 0.45 meq/L of Pb(II)] having total initial metal ion concentration of 0.60 meq/L till the bed was again exhausted or yielded effluents with more than 80% of initial metal ion concentration. The breakthrough curves are shown in Fig. 4. When the virgin bed was loaded with combination–I of binary–metal ion system, there was no residual concentration of Cu(II) and Pb(II) metal ions into the effluent from GAA bed in the first 210 min. of operation. After initial 210 min., the residual concentration of Pb(II) started to increase slowly while the residual concentration of Cu(II) ion increased rapidly and reached to a value of 0.150 meq/L. As the operation continued, the bed got exhausted with respect to Cu(II), Pb(II) and total metal ion in 3270, 6000 and 4970 min. respectively. The virgin bed exhausted with combination–I of binary–metal system was washed and then reloaded with working solution of combination–II of binary–metal system. It yielded a relatively steep breakthrough curve for Pb(II) metal (Fig. 4). The washed exhausted bed re–exhausted with respect to Pb(II) metal ion in approximately 1365 min. of operation. During reloading of the washed bed with combination–II of binary–metal system, displacement of Cu(II) ions from the bed took place. It was also observed that when the concentration of displaced Cu(II) was decreasing at a faster rate, the breakthrough curve of Pb(II) ion for washed exhausted bed showed an increasing trend at relatively faster rate and appeared to get saturated when displacement of Cu(II) became almost negligible. The variation in concentration of displaced Cu(II) ions from the bed is also presented in Fig. 4.

[431] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II)

Fig. 4: Breakthrough Curves for Virgin GAA Bed Exhausted with Combination–I of Binary–Metal Ions and Washed Exhausted Bed Reloaded with Combination–II of Binary–Metal Ions [Initial Metal Conc. in Combination–I: Cu(II) = 0.45±0.01 meq/L + Pb(II) = 0.15±0.02 meq/L and Combination–II: Cu(II) = 0.15±0.00 meq/L + Pb(II) = 0.45±0.01 meq/L, Initial Adjusted pH = 4.9±0.1, Effluent pH = 5.5±0.6; Temp. = 30±1 oC] Mass balance of metal retained in the virgin bed from combination–I of binary–metal ion system was carried out for a time period when Cu(II) concentration in the effluent was less than or equal to 50% of the influent total metal concentration. Similarly mass balance of metal retained in the washed exhausted bed from combination–II of binary–metal ion system was carried out for a time period when Pb(II) concentration in the effluent was less than or equal to 50% of the influent total metal concentration. In the case of the virgin bed, exhaustion time (tE) with respect to Cu(II) ion came out to be 2730 min. The amount of Cu(II), Pb(II) and total metal retained in virgin bed upto 2730 min. was estimated as 0.770, 0.358 and 1.128 meq respectively. The exhausted bed was washed to remove un–adsorbed metal ions from pore volumes of the bed. The amount of un–adsorbed Cu(II), Pb(II) and total metal in the washings was estimated as 0.022, 0.016 and 0.038 meq respectively. After washing, the exhausted bed was reloaded with combination–II of binary metal ion system and exhaustion time (tE) with respect to Pb(II) ion came out to be 750 min. The amount of Pb(II) retained on the bed up to 750 min. was estimated as 0.201 meq and 0.121 meq of Cu(II) was displaced from the bed. Hence the total metal retained on the bed was estimated as 1.170 meq and the total metal retained per unit weight of the adsorbent was estimated as 0.124 meq/g.

3.4 Breakthrough Curves for Virgin GAA Bed Exhausted with Combination–II of Binary–Metal System and Reloaded with Combination–I of Binary-Metal System The breakthrough curves for virgin bed loaded with working solutions of combinations–II of binary–metal ions followed by reloading of washed exhausted bed with working solution of combination–I of binary– metal ions is presented in Fig. 5. When the virgin bed was loaded with combination–II of binary–metal [432] Cu(II) and Pb(II) Uptake by Granular Activated Alumina Columns Exposed to Mono–and Binary–Metal Ion Systems ion system, there was complete removal of Cu(II) and Pb(II) metal ion from the working solution in the first 300 min. of operation. After 300 min., the breakthrough curve for Cu(II) started to increases slowly while the breakthrough curve for Pb(II) and total metal ion increased rapidly and reached to a value of 0.314 and 0.379 meq/L respectively in 1250 min. The bed got exhausted with respect to Cu(II), Pb(II) and total metal ion in 2550, 1570 and 2185 min. respectively. The virgin bed exhausted with combination– II of binary–metal system was washed and then reloaded with working solution of combination–I of binary–metal system. It yielded a relatively steep breakthrough curves for Cu(II), Pb(II) and total metal (Fig. 5). The washed exhausted bed re–exhausted with Pb(II), Cu(II) and total metal ion in approximately 2440, 2680 and 2680 min. of operation.

Fig. 5: Breakthrough Curves for Virgin GAA Bed Exhausted with Combination–II of Binary–Metal Ions and Washed Exhausted Bed Reloaded with Combination–I of Binary–Metal Ions [Initial Metal Conc. in Combination–I: Cu(II) = 0.45±0.01 meq/L + Pb(II) = 0.15±0.02 meq/L and Combination–II: Cu(II) = 0.15±0.01 meq/L + Pb(II) = 0.45±0.02 meq/L, Initial Adjusted pH = 4.9±0.0; Effluent pH = 5.6±0.5; Temp. = 30±1 oC] The mass balance of metal retained in the virgin bed from combination–II of binary–metal ion system was carried out for a time period when Pb(II) concentration in the effluent was less than or equal to 50% of the influent total metal concentration. Similarly mass balance of metal retained in the washed exhausted bed from combination–I of binary–metal ion system was carried out for a time period when Cu(II) concentration in the effluent was less than or equal to 50% of the influent total metal concentration.

In the case of the virgin bed loaded with combination–II of binary–metal ion system, exhaustion time (tE) with respect to Pb(II) ion came out to be 1050 min. The amount of Pb(II), Cu(II) and total metal retained in virgin bed up to 1050 min was estimated as 0.441, 0.132 and 0.573 meq respectively. The exhausted bed was washed to remove un–adsorbed metal ions from pore volumes of the bed. The amount of un–adsorbed Pb(II), Cu(II) and total metal was estimated as 0.017, 0.006 and 0.023 meq respectively. After washing, the exhausted bed was reloaded with combination–I of binary metal ion system and exhaustion [433] e-Book: 2nd National Conference on Recent Advances in Civil Engineering (RACE-II) time (tE) with respect to Cu(II) ion came out to be 1930 min. The amount of Cu(II), Pb(II) and total metal retained on the bed upto 1930 min. was estimated as 0.148 meq, 0.527 meq and 0.675 meq respectively. Hence the total metal retained on the bed was estimated as 1.225 meq and the total metal retained per unit weight of the adsorbent was estimated as 0.130 meq/g.

4. SUMMARY The results obtained from column studies for mono– and binary–metal systems under uncontrolled pH conditions are summarized below. 1. The results of column studies with mono–metal systems indicates that the metal uptake by virgin bed is higher for Cu(II) than Pb(II). 2. In binary–metal ion systems, the metal uptake by virgin bed is higher for combination–I of binary metal ion system than combination–II of binary metal ion system. 3. In mono–metal ion system, when already exhausted GAA bed reloaded with another metal ion the uptake of another metal ion is observed along with displacement of already adsorbed metal ion. 4. In binary–metal ion system, when virgin bed loaded with combination–I of binary metal ion system and washed exhausted bed reloaded with combination–II of binary–metal ions system, again the uptake of Pb(II) and displacement of Cu(II) from GAA bed is observed. However, uptakes of Cu(II) and Pb(II) is observed and no displacement of either Cu(II) or Pb(II) is observed when virgin bed loaded with combination–II of binary metal ion system and washed exhausted bed reloaded with combination–I of binary–metal ions system.

REFERENCES [1] Ahmad, A.A., Hameed, B.H., Aziz, N. 2007. Adsorption of direct dye on palm ash: Kinetic and equilibrium modeling. Journal of Hazardous Materials, 141(1), 70-76. [2] Aklil, A., Mouflih, M., Sebti, S. 2004. Removal of heavy metal ions from water by using calcined phosphate as a new adsorbent. Journal of Hazardous Materials, 112(3), 183-190. [3] Cardoso, F.C., Sears, W., LeBlanc, S.J., Drackley, J.K. 2011. Technical note: Comparison of 3 methods for analyzing areas under the curve for glucose and nonesterified fatty acids concentrations following epinephrine challenge in dairy cows. Journal of Dairy Science, 94(12), 6111-6115. [4] Dwivedi, C.P., Sahu, J.N., Mohanty, C.R., Mohan, B.R., Meikap, B.C. 2008. Column performance of granular activated carbon packed bed for Pb(II) removal. Journal of Hazardous Materials, 156(1–3), 596-603. [5] Febrianto, J., Kosasih, A.N., Sunarso, J., Ju, Y.-H., Indraswati, N., Ismadji, S. 2009. Equilibrium and kinetic studies in adsorption of heavy metals using biosorbent: A summary of recent studies. Journal of Hazardous Materials, 162(2–3), 616-645. [6] Gupta, V.K., Gupta, M., Sharma, S. 2001. Process development for the removal of lead and chromium from aqueous solutions using red mud—an aluminium industry waste. Water Research, 35(5), 1125-1134. [7] Gupta, V.K., Jain, C.K., Ali, I., Sharma, M., Saini, V.K. 2003. Removal of cadmium and nickel from wastewater using bagasse fly ash—a sugar industry waste. Water Research, 37(16), 4038-4044. [8] Han, R., Zhang, J., Zou, W., Xiao, H., Shi, J., Liu, H. 2006. Biosorption of copper(II) and lead(II) from aqueous solution by chaff in a fixed-bed column. Journal of Hazardous Materials, B133, 262-268. [9] Hawari, A.H., Mulligan, C.N. 2007. Effect of the presence of lead on the biosorption of copper, cadmium and nickel by anaerobic biomass. Process Biochemistry, 42(11), 1546-1552. [10] Karimi, M., Shojaei, A., Nematollahzadeh, A., Abdekhodaie, M.J. 2012. Column study of Cr (VI) adsorption onto modified silica–polyacrylamide microspheres composite. Chemical Engineering Journal, 210(0), 280-288. [11] Liu, Z.-r., Zhou, L.-m., Wei, P., Zeng, K., Wen, C.-x., Lan, H.-h. 2008. Competitive adsorption of heavy metal ions on peat. Journal of China University of Mining and Technology, 18(2), 255-260. [12] Öztürk, N., Kavak, D. 2005. Adsorption of boron from aqueous solutions using fly ash: Batch and column studies. Journal of Hazardous Materials, 127(1–3), 81-88. [13] Pauling, L. 1960. The Nature of the Chemical Bond. Cornell University Press. [14] Sawyer, C.N., McCarty, P.L., Parkin, G.F. 2003. Chemistry for Environmental Engineering and Science. 4th ed. Tata McGraw-Hill, New Delhi.

[434] Author Index Ahmad, Vashi, 249 Mahajan, Abhishek Dnyaneshwar, 140 Anurag, 42 Maheshwari, U.K., 192, 314 Arshad, Shaikh, 106 Maurya, Alok Kumar, 296 Mhaske, Sumedh, 77, 88, 106 , 112 , 134 , 140 Bala, Amit Kumar, 356 Mishra, Alok Kumar, 192 Bane, Abhishek Arvind, 134 Mohan, Mani, 42 Burman, A., 166, 174 Burrewar, Smita, 282 Narnoli, Vishal Kumar, 351 Nishant, Naveen, 284 Chakrabarty, Shuvodeep, 205 Chaturvedi, Nikhil Kumar, 192 Pandey, Animesh, 308 Chaudhari, Pravin, 227 Paradhan, M.K., 205 Chauhan, Digvijay Singh, 88 Paras, Nath Rai, 402, Choudhary, Rajan, 147 Patel, Amit, 407 Patidar, S.K., 266 Das, Bijay Kumar, 284 Poredi, Sarvesh, 112 Dheeraj, V.P., 5 Prakash, Abhinav, 236 Ganesan, S., 415 Prakash, Gautam, 256 Gautam, R., 174 Prakash, Rohan, 64 Gharat, Nikhil, 59 Prasad, Brajkishor, 407, 415 Gupta, Nakul, 161, 182 Praveen, K., 308 Gupta, Rajesh, 122 Quaff, A.R., 18, 5 Honkalas, Prasanna, 50 Raj, Anshu, 374 Jawed, Mohammad, 425 Raj, Sudhanshu, 72 Jha, Madan K., 1 Rajak, Fulena, 284 Rajpoot, Komal, 266 Kar, Saurav Shekhar, 220 Ranjan, Manish Kumar, 374 Kumar, Abhinay, 147 Ranjan, Shashi, 374 Kumar, Abhishek, 14 Rawat, Vishal Singh, 72 Kumar, Ajay, 296, 356, 380 Reddy, G.R., 205 Kumar, Amrendra, 156 Roshni, Thendiyath, 1 Kumar, Anjneya, 199 Roy, Koushik, 199 Kumar, Ankush, 147 Roy, L.B., 220, 236, 242, 302, 308, 366 Kumar, Deepak, 30 Rushad, Syed Tabin, 14 Kumar, Gaddam Vinay, 72 Kumar, Gaurav, 366 Sagvekar, Siddhesh D., 275 Kumar, Pappu, 216 Sah, Dukhi, 373 Kumar, Rajnish, 339 Samui, Pijush, 1 Kumar, Ravish, 295, 296, 380 Sarangi, Sagar, 42 Kumar, S., 174 Saxena, N.K., 314 Kumar, Sandeep, 72 Saxena, Shivangi, 242 Kumar, Santosh, 321 Sengupta, Siddhartha, 30, 95 Kumar, Saurabh, 18 Sharma, Anjali, 282, 283, 284, 295, 296 Kumar, Suraj, 1, 220 Sharma, Madhavendra, 325 Kumar, Vikram, 37 Singh, Anshuman, 216 Kumari, Sunita, 156 Singh, Anurag, 220 Kumari, Supriya, 380 Singh, Arpan, 14 [435] Author Index Singh, Bhupendra, 77 Thendiyath, Roshni, 72 Singh, Bibhakar Kumar, 95 Tiwari, Aman, 236 Singh, Diksha, 314 Tiwary, Kanvi, 283, 295 Singh, Prince, 407, 415 Tobby, Agwe Michael, 249 Singh, Shubham, 302 Singh, Upendra K., 392 Upadhayaya, Ashutosh, 236 Singh, V.K., 166 Varekar, Vikas, 50, 59 Singh, Vikash, 249 Varshney, Deepak, 161, 182 Singh, Vivekanand, 374 Verma, Anand Prabhat, 161, 182 Sinha, Sanjeev, 406 Verma, Rajnikant, 332 Sonawane, Durgesh, 227 Soni, Atul, 161, 182 Wayal, A.S., 275 Sonkar, Brijesh Kumar, 249 Yadav, Manoj Kumar, 425 Srinivas, K., 205 Suman, S.K., 64, 256, 325, 332, 339, 351 Zaman, Bushra, 401

[436] -Book e-ISBN: 978-93-89947-11-3

2nd National Conference on Recent Advances in Civil Engineering RACE–II 6th –7th June, 2019

Organized by Department of Civil Engineering National Institute of Technology Patna Ashok Rajpath, Patna – 800005 Bihar

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