A novel strategy for generating mesoscale asphalt concrete model with controllable aggregate morphology and packing structure

Abstract

Establishing a mesoscale model of asphalt concrete is significantly challenging due to its inherent heterogeneity and high proportion of aggregates. Initially, a novel approach for systematically quantifying aggregate morphology by integrating both form scaling and spherical harmonic (SH) modeling is formulated. The proposed method excels in decomposing aggregate morphology at diverse length scales and accurately quantifying non-star-like and flat aggregates. Subsequently, Principal Component Analysis (PCA) is performed on the quantified morphology parameters to produce sufficient virtual aggregates with similar morphology to the real ones. Finally, the robust Bullet physics engine is employed to compact the generated aggregates, which can develop an aggregate packing structure closely resembling real asphalt concrete. Besides, the aggregate morphology and gradation of the generated packing structure can be effectively controlled. Through additional geometry and mesh processing, high-fidelity mesoscale models of asphalt concrete can be generated. This novel strategy lays the foundation for further mechanical modeling on asphalt concrete.