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Random Modeling of Three-Dimensional Heterogeneous Microstructure of Asphalt Concrete for Mechanical Analysis.

Authors :
Chen, Jiaqi
Wang, Hao
Dan, Hancheng
Xie, Youjun
Source :
Journal of Engineering Mechanics; Sep2018, Vol. 144 Issue 9, p1-11, 11p
Publication Year :
2018

Abstract

This paper develops an algorithm for generating the three-dimensional (3D) heterogeneous microstructure of asphalt concrete based on random modeling. The asphalt concrete was modeled as heterogeneous material with fine aggregate matrix (FAM), coarse aggregates, and air voids. We generated 3D aggregate shapes with three two-dimensional (2D) projections randomly selected from the aggregate image database. We generated the 3D models of asphalt concrete by randomly placing 3D aggregates and air voids into the virtual specimen with compact packing. We predicted the dynamic modulus of asphalt concrete specimens with different microstructures through finite element (FE) analysis and validated with experimental data. The relative differences between the average dynamic modulus and the experimental data ranged from 0.32 to 6.01% for different frequencies, which indicates that the 3D heterogeneous microstructure model is acceptably accurate. The volume of aggregate in each sieve is the major factor controlling bulk material properties like dynamic modulus. We also generated 2D heterogeneous models of asphalt concrete by cutting the 3D model from different cross sections. The variation of dynamic modulus with the 2D models was much greater than the variation with the 3D models. The ratio of coarse aggregate content in the 2D and 3D models can range from 0.86 to 1.35. Although, in general, the predicted dynamic modulus increases as coarse aggregate content increases in 2D models, we observed variations due to differences in microstructure. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07339399
Volume :
144
Issue :
9
Database :
Complementary Index
Journal :
Journal of Engineering Mechanics
Publication Type :
Academic Journal
Accession number :
142026957
Full Text :
https://doi.org/10.1061/(ASCE)EM.1943-7889.0001505