Prediction Model on Permeability Coefficient of Porous Asphalt Concrete under Repeated Clogging Based on Void Characteristic Parameters

Abstract

Porous asphalt concrete (PAC) is commonly applied in locations with heavy rainfall. However, because of the mix’s characteristics and service environment, it is impossible to ensure the duration of its permeability performance. This paper explores the aspects that influence PAC’s permeability performance. A comprehensive clogging model is also developed, which includes PAC mix parameters. First, three clogging materials were produced. Second, the effect of nominal maximum aggregate size, porosity, and clogging material on PAC’s permeability is discussed. Finally, models are proposed to predict PAC’s clogging factor β and clogging times N. The results revealed that the remaining PAC mix parameters, except for the nominal maximum aggregate size, were associated strongly with the β and N. The prediction models established for β and N in PAC mixes were highly reliable, with correlation values over 0.90 in all cases. In addition, the mixture parameters that had the greatest influence on the clogging factor β and clogging times N are differed. The uniformity and curvature coefficients influenced the clogging factor β the most, while the initial permeability coefficient affected the clogging times N the most.