Development of Prediction Model for Structural Behavior and Gradation of Porous Asphalt Pavement

Abstract

Abstract This study is aimed at developing a prediction model for structural behavior of Porous Asphalt Pavement (PAP) using ABAQUS and also developing ANN model to predict void percentages in Porous Asphalt gradation mixes. Data from the past literature was used to analyze various mixing parameters affecting the properties of Porous Asphalt gradation mix. PAP was analyzed using KENPAVE software and the results revealed that lesser number of allowable repetitions to fatigue and rutting failures were observed for lesser Porous Asphalt Concrete (PAC) layer thicknesses. Nature of subgrade material was found to influence the rutting performance of PAP with clayey soils showing 77.74% reduction in design life of pavement as compared to gravelly soil subgrade. Higher contact pressures resulted in higher tensile stresses at the bottom of PAC layer which in turn reduced the fatigue life of PAP. Results from ABAQUS revealed that increase in void percentage in PAC mix resulted in significant increase in horizontal tensile strain at the bottom of PAC layer by 12.3% and increased tensile strain for 28% void in total mix than for 16% voids. Thus, leading to 92.8% reduction in allowable load repetitions to fatigue failure. Also, increased void percentage led to decrease in vertical stress and deflection in PAP but no significant effect on allowable repetitions to rutting failure was found. Asphalt Pavement mixes were also compiled to develop ANN prediction model. The results indicate good conformity between predicted and actual data with mean square error of 0.109 and coefficient of correlation as 0.994.