Predicting Asphalt Pavement Macrotexture Depth in Discrete Element Method

Abstract

Pavement macrotexture plays an important role in determining tire-pavement frictional characteristics, which are critical for users safety. This study introduces a numerical modelling to simulate asphalt mixture based on Discrete Element Method (DEM), for predicting surface macrotexture depth under various mix conditions. The proposed model incorporates comprehensive parameters of asphalt mixture, including aggregate gradation, percentage of bitumen, density of aggregates and bitumen, and air voids. Model validation was conducted using on-site measurements of Height of Sand (HS) over a new paved road section. The comparisons of macrotexture depth between on-site HS and numerical prediction out of the proposed model show the robustness and reliability of this approach. The findings highlight the model potential to analyze pavement macrotexture depth effectively, with enhanced precision over empirical formula by integrating sufficient parameters of asphalt mixture.