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Cracking Models for Use in Pavement Maintenance Management

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Cracking Models for Use in Pavement Maintenance Management Cracking Models for Use in Pavement Maintenance Management Adelino Ferreira1, Rui Micaelo2, and Ricardo Souza1 1 Department of Civil Engineering, University of Coimbra, Portugal {adelino,ricardosouza}@dec.uc.pt 2 Department of Civil Engineering, Universidade Nova de Lisboa, Portugal [email protected] Abstract. With the recent approval of the Portuguese Law No. 110/2009 of 18 May, within the scope of road concession contracts, the concessionaires need to submit to the Portuguese Road Infrastructures Institute a Quality Control Plan (QCP) and a Maintenance and Operation Manual (MOM). These documents require the revision of current Pavement Management Systems to consider pavement performance prediction models for each pavement state parameter so that it permits time definition of maintenance and rehabilitation (M&R) interventions for the fulfilment of the values defined in the QCP in each year of the concession period. The QCP presents the admissible values for each pavement state parameter (cracking, rutting, roughness, etc.) that a concessionaire of highways needs to verify. Nevertheless, a concessionaire, beyond the annual pavement inspections to demonstrate the fulfilment of the QCP, wants to predict the proper time to apply M&R preventive interventions at a minimum cost for the complete concession period. This paper describes the state-of-the-art in terms of cracking models. The selected models evaluate the cracking area evolution for a set of representative Portuguese pavements structures and traffic conditions. The Indian and HDM-4 deterioration models were considered to be the most promising to implement in a new Portuguese Maintenance Optimisation System, i.e. to provide a good solution to the pavement maintenance management problem involving not only periodic maintenance but also routine maintenance (crack sealing, rut levelling, patching, etc.). 1 Introduction A Pavement Management System (PMS) can be defined as a set of tools which helps a road network administration to optimize maintenance and rehabilitation (M&R) actions for keeping the pavements in good service condition. One of the modules of a PMS is the Pavement Performance Model (PPM), which is a mathematical representation that can be used to predict the future state of pavements, based on current state, deterioration factors and effects resulting from M&R actions [1]. Currently the PMS of Estradas de Portugal S.A., the Portuguese A. Scarpas et al. (Eds.), 7th RILEM International Conference on Cracking in Pavements, pp. 429–439. © RILEM 2012 430 A. Ferreira, R. Micaelo, and R. Souza Road Administration, uses for PPM the AASHTO pavement performance model that computes a global pavement condition index, the present serviceability index (PSI), based on several factors like the traffic, the material properties and the drainage and environmental conditions [2]. The extent and severity of distresses at the time that the pavement condition index reaches the warning level restricts the implementation of more cost-effective techniques [3]. In 2007 and 2009 the Portuguese Government published legislation [4, 5] established EP – Estradas de Portugal, S.A., as the global road network concessionaire and the basis of the concession contract. Within this contract it was established that concessionaires have to submit to the Portuguese Road Infrastructures Institute (InIR), the supervisor institution, on a regular basis, a Quality Control Plan (QCP) and a Maintenance and operation Manual (MOM). The QCP defines the limits of pavement condition parameters (rutting, cracking, roughness, etc.) than can be found at any time of the concession period. Therefore, these two documents, specially the first one, require knowing the pavement condition ahead, not only the general pavement service condition, but quantifying the extent and the magnitude of pavement distresses and the actions to be implemented in every situation. When a concessionaire does not fulfil the QCP, InIR can apply a contractual infraction, in which the global sum varies, according to its gravity, between €5,000 and €100,000, or daily values that can vary between €500 and €5,000 [4]. A concessionaire, beyond the annual pavement inspections to demonstrate to the InIR and the concessor (the Portuguese State or represented by the EP - Estradas de Portugal, S.A.) the fulfilment of the QCP, wants to predict the year when their pavements do not fulfil the admissible values for some state parameter. A concessionaire knowing this information can apply M&R preventive interventions at a minimum cost in order to effectively fulfil the QCP in all the remaining years of the concession period. This paper describes the state-of-the-art in terms of cracking models, and evaluates the performance of the selected models considering the cracking area evolution for a set of representative Portuguese pavements structures and traffic conditions. 2 Cracking Prediction Models In this study, the methodology used was to analyse several pavement cracking deterioration models available in the literature with the objective of its integration in the Portuguese Pavement Management Systems. The models selected are the following ones: the Brazilian model; the PAVENET-R model; the HDM-4 model; the Ker Lee Wu (KLW) model; the Indian model; and the Austroads model. 2.1 Brazilian Model (1994) This model was developed by Visser, Queiroz and Caroca [6] based on a long- term pavement monitoring program carried out in Brazil between 1975 and 1985. The road sections were unbound granular base flexible pavements in areas with tropical to subtropical climate with an average annual precipitation between 1200 Cracking Models for Use in Pavement Maintenance Management 431 and 1700 mm/year. Cracked area over time is predicted with Eqn. (1), developed with multiple regression and probabilistic time failure analysis, which depends on traffic volume, the pavement bearing capacity (load deflection) and age. For existing pavements with asphalt surfacing the model only applies to cracking progression prediction, while for asphalt overlays and slurry seals the model comprises two-phases, initiation time and progression prediction. Two-phase models give an extra opportunity to calibrate the model for cracking prediction over time. This model considers the Benkelman beam to measure pavement deflections, but this equipment is not used in Europe any more. However, some regressions relating the modified structural number with the Benkelman beam maximum deflection have been proposed by several authors such as Eqn. (2) by Paterson [7, 8]. The modified structural number is the evolution of the AASHTO structural number by considering the subgrade contribution. − C = (B ×10 2 )× log()(N80c × 0.0456 + 0.00501×Y )−18.53 − C (1) t t t 0 − SNC= 3.2× B 0.63 (2) Where Ct is the pavement cracked area (class 2 cracking or worse, i.e. crack width 2 2 larger than 1 mm) in year t (m /100m ); Yt the age of pavement since original construction or since subsequent AC overlay (years); N80ct is the cumulative 80 kN equivalent single axle load (ESAL) at age t (ESAL/lane); B is the Benkelman beam maximum deflection for the existing pavement (mm); C0 is the cracking offset term calculated to ensure that predicted cracking conforms with the initial value at the start of analysis; SNC is the modified structural number. 2.2 PAVENET-R Model (1996) The cracking prediction model defined by Eqn. (3) is used in the computer model PAVENET-R [9] aiming at the optimization of the maintenance-rehabilitation problem at the network level. The cracked area over time is predicted based on traffic and the pavement AASHTO structural number calculated using Eqn. (4). As for the previous model it is an only one phase model (just dealing with progression) and it does not include a variable that accounts for the existing cracked area at the beginning of the analysis. − C = 617.14× N80c × SN SN (3) t t N = × e × d SN Hn Cn Cn (4) n=1 2 2 Where Ct is the total cracked area in year t (m /100m ); N80ct is the cumulative equivalent standard axle load (ESAL) at age t (million ESAL/lane); SN is a e d structural number; Cn is the structural coefficient of layer n; Cn is the drainage coefficient of layer n; and Hn is the thickness of layer n (mm). 432 A. Ferreira, R. Micaelo, and R. Souza 2.3 INDIAN Model (1994) The Indian model was derived from a pavement performance study carried out during the 90’s with extensive monitorisation of pavement sections (145) along national and state highways in four Indian states [10]. The cracking prediction model is a two-phase model, considering the time to cracking initiation calculated using Eqn. (5), and the cracking progression calculated using Eqn. (6). As for the previous models, just two variables were included (traffic and the pavement structural number). The model is applicable to pavements with asphalt surfacing (excluding surface dressing and slurry seal). The climate where the pavement data was gathered varies from arid to humid subtropical, being far from the Portuguese Mediterranean climate. n×N 80c −1.09× 1 = × SNC 2 (5) Tci 4.00 e × ()− 0.65 = + × n N80ct N80cti × 0.32 × ()− Ct C i 4.26 SCi t ti (6) SNC Where Tci is the time to structural cracking initiation (years) - Ct = 2.0%; Ct is the 2 2 total cracked pavement area in year t (m /100m ); N80ct is the cumulative 80 kN equivalent single axle load (ESAL) at age t (million ESAL/lane); N80cTci is the cumulative 80 kN equivalent single axle load (ESAL) at age of cracking initiation (million ESAL/lane); SNC is the modified structural number for the pavement; n is the number of lanes in the road section; Ci is the total cracked pavement area at the 2 2 beginning of the analysis period (m /100m ); ti is the time at the beginning of the 2 2 analysis period (years); SCi is the minimum of {Ci; 100 - Ci} (m /100m ).
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