Establishing prediction master curve of dynamic modulus of asphalt mixture considering randomness of aggregate morphology

Abstract

The objective of this paper is to study the influence of aggregate morphology on dynamic modulus of asphalt mixture and establish a method to predict dynamic modulus of asphalt mixture at different temperatures and loading frequencies based on aggregate morphology and asphalt mortar material parameters. The Digital image processing (DIP) method is used to obtain statistical laws of the fractal dimension D and aspect ratio lw of aggregate section profiles, and the midpoint displacement method is used to generate virtual random aggregate sections. Based on the 2P2S1D constitutive model using the WLF time temperature equivalence, master curves of dynamic modulus of asphalt mortar at different reference temperatures are obtained and converted into the Prony series. Interface Transition Zones (ITZs) between asphalt mortars and aggregates are modeled by the Coulomb friction model, and dynamic moduli of asphalt mixture calculated by this model are in the range of calculation results by the tie model and the frictionless model. A total of 100 virtual specimens including random aggregates, asphalt mortars, ITZs and air voids are generated. Under different temperature and frequency combinations, extensive virtual tests of dynamic modulus of asphalt mixture are carried out on the virtual specimens. Based on the virtual test data of dynamic modulus, prediction master curves of dynamic modulus of asphalt mixture are obtained. The results show that aggregate morphology has a significant effect on dynamic moduli of asphalt mixture, and this effect has a clear correlation with the distribution laws of aggregate morphology indexes. By comparing with the test data of different literature, the probabilistic prediction method of dynamic modulus of asphalt mixture established in this paper is feasible.