Hydrostatic Performance of Reinforced Concrete Pipe for Infiltration
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Western University Scholarship@Western Electronic Thesis and Dissertation Repository 9-9-2020 11:30 AM Hydrostatic Performance Of Reinforced Concrete Pipe For Infiltration Lui Sammy Wong, The University of Western Ontario Supervisor: Nehdi, Moncef L., The University of Western Ontario A thesis submitted in partial fulfillment of the equirr ements for the Doctor of Philosophy degree in Civil and Environmental Engineering © Lui Sammy Wong 2020 Follow this and additional works at: https://ir.lib.uwo.ca/etd Part of the Civil Engineering Commons Recommended Citation Wong, Lui Sammy, "Hydrostatic Performance Of Reinforced Concrete Pipe For Infiltration" (2020). Electronic Thesis and Dissertation Repository. 7397. https://ir.lib.uwo.ca/etd/7397 This Dissertation/Thesis is brought to you for free and open access by Scholarship@Western. It has been accepted for inclusion in Electronic Thesis and Dissertation Repository by an authorized administrator of Scholarship@Western. For more information, please contact [email protected]. ABSTRACT Groundwater infiltration into underground sewer systems has long been a costly issue for municipalities. With reinforced concrete pipe (RCP) being a primary option for sewer systems, existing hydrostatic testing methods conducted by manufacturers to measure internal pipe pressure, as required by specifications, do not reflect in-situ external hydrostatic conditions. This thesis records the development of a novel testing method to evaluate the RCP joint performance for infiltration. The test is safe and easy to conduct by RCP producers at the factory. The test method mimics field conditions of possible RCP joint gap and joint offset. Over 100 tests were conducted, including 600 mm, 900 mm and 1200 mm RCP with conventional single offset self-lubricated gaskets. This study also evaluates the gasket performance for infiltration. Pipe joint performance curves were developed based on the test results. Comparison to laboratory load-deformation tests on gaskets was conducted, indicating that predictions of the sealing potential derived using gasket geometry agreed well with the results of infiltration tests. The study shows that the joint gap plays an important role in the sealing potential. The developed apparatus allows the observation of gasket movement under infiltration pressure against the gasket leading to failure. The performance curves also allow the prediction of an infiltration potential leading to a practical applicational procedure to guide RCP installation. A case study of deep RCP pipe subjected to groundwater pressure illustrated the usefulness of the performance curves to derive maximum allowable joint gaps, which contractors could rely on during RCP installation. The findings should allow deducing technical guidance on how water tightness of RCP can be achieved at installation below the prevailing groundwater level. Two oversampling methods: Synthetic Minority Over-sampling Technique (SMOTE) and Density-Based SMOTE, were employed to address the unbalanced dataset. Accordingly, applying advanced machine learning techniques, the scale of variation in the test data can be analyzed and accurately predicted using tree-based supervised classification methods: random forest, extra trees and gradient boosting. ii Keywords Concrete pipe; Infiltration; Joint; Performance; Hydrostatic Pressure; Test; Machine Learning; Supervised Learning; Gradient Boosting; SMOTE, DBSMOTE. iii SUMMARY FOR THE LAY AUDIENCE Groundwater infiltration into sewer systems is a costly problem for many municipalities. With reinforced concrete pipe (RCP) being one of the most commonly used pipe options for sewer systems, existing hydrostatic testing methods conducted by manufacturers measuring internal pressure do not reflect in-situ external hydrostatic conditions. This thesis presents the development of a novel testing method to evaluate the RCP joint performance for infiltration. The test is safe and easy to conduct by RCP producers at the factory. The test also mimics the field conditions of possible joint gaps and joint offsets. The test procedure was repeated many times for 600 mm, 900 mm and 1200 mm RCP. The performance of commonly used single offset self-lubricated gaskets and various alignments were evaluated. Performance curves were developed based on the testing results. Comparisons to the laboratory load-deformation tests on gaskets were also conducted, indicating that predictions of the sealing potential derived using gasket geometry agreed with the results of the infiltration tests. The study shows that the joint gap plays an important role in the sealing potential. The apparatus developed allows the observation of gasket movements under infiltration pressures against the gasket leading to failure. The performance curves also allow the prediction of an infiltration potential leading to a practical applicational procedure to guide the installation of the pipe. A case study of deep RCP pipe subjected to groundwater pressure illustrated the usefulness of the performance curves to derive maximum allowable joint gap, which contractors could rely on during RCP installation. The findings should allow deducing technical guidance on how water tightness of RCP can be achieved at installations below the prevailing groundwater level. Lastly, with the application of advanced machine learning techniques, the scale of the variation in the test data can be analyzed and predicted using classification methods. The modeling technique, procedure and accuracy evaluation are presented. iv CO-AUTHORSHIP STATEMENT This thesis was prepared according to the integrated-article layout designated by the Faculty of Graduate Studies at Western University, London, Ontario, Canada. All the work stated in this thesis, including experimental testing, data analysis, machine learning models, and writing of draft manuscripts for publication, was carried out by the candidate under the supervision and guidance of Professor M.L. Nehdi. Any other co-authors assisted in conducting the experimental program and/or revision of the initial draft of the manuscript. The following publications have been either published, accepted or submitted to peer-reviewed technical journals and international conferences: Wong, L. and Nehdi, M.L. (2018) Critical Analysis of Precast Concrete Pipe Standards, Infrastructures, 3(3), 18 p. ; https://doi.org/10.3390/infrastructures3030018 Wong, L. and Nehdi, M.L. (2018) New Test Method for RCP Joint Hydrostatic Infiltration, CSCE Conference 2018, Fredericton, New Brunswick, Canada. Wong, L. and Nehdi, M.L. (2020, In Press) Quantifying Resistance of Reinforced Concrete Pipe Joints to Water Infiltration, ASCE Journal of Pipeline Systems - Engineering and Practice. Wong, L. and Nehdi, M.L. (2020, Submitted) Predicting Hydrostatic Infiltration in Reinforced Concrete Sewer Pipes Considering Joint Gap and Joint Offset, ASCE Journal of Pipeline Systems - Engineering and Practice. Wong, L., Marani, A. and Nehdi, M.L. (2020, Submitted) Coupled Gradient Boosting – Ensemble Oversampling Hybrid Model for Prediction of Concrete Pipe Joint Infiltration, ASCE Journal of Pipeline Systems - Engineering and Practice. v DEDICATION To: My Wife: Grace Tsoi My Children: Kalos Wong and Charis Wong My Parents: Wa Chan, Kan Chuen Wong vi ACKNOWLEDGMENTS Professor M. L. Nehdi – supervisor and mentor, his encouragement, vision and guidance, allowed me to open doors to the new field of machine learning in Con Civil Engineering. Brian Wood – President at Con Cast Pipe, my former employer, for his financial support and his vision in the industry and pursuing innovation. Con Cast Pipe – Support in the space and technical staff (Andrew Cleland, James Cameron, Tien Nguyen) at different stages of the experimental program. Press Seal Corporation and Hamilton Kent – supplies of gasket samples, and their technical inputs, laboratory for material testing. James Malpass, P.Eng. – technical mentor, his practical experience and guidance provided great help. Being a distant student, he welcomed me to stay at his place for certain occasions such as inclement weather or examinations. vii TABLE OF CONTENTS ABSTRACT ....................................................................................................................... ii CO-AUTHORSHIP STATEMENT ................................................................................ v ACKNOWLEDGMENTS .............................................................................................. vii TABLE OF CONTENTS .............................................................................................. viii LIST OF TABLES ......................................................................................................... xiii LIST OF FIGURES ........................................................................................................ xv LIST OF NOMENCLATURE ...................................................................................... xix LIST OF ABBREVIATION.......................................................................................... xxi LIST OF APPENDICES ............................................................................................. xxiii PREFACE ..................................................................................................................... xxiv CHAPTER 1 ....................................................................................................................... 1 1 Introduction ...................................................................................................................