Size Effects of Finite Element Model for Three-Dimensional Microstructural Modeling of Asphalt Mixture

Asphalt mixture is a particulate composite material consisting of aggregate, mastic, and air voids. The computed tomography (CT) image-based finite element approach is used as an effective method to simulate micromechanical response of asphalt mixture. For finite element analysis, the accuracy of th...

Full description

Saved in:
Bibliographic Details
Main Authors: Kuanghuai Wu, Qingzi Deng, Naiming Deng, Xu Cai, Wenke Huang
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2019/1754567
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Asphalt mixture is a particulate composite material consisting of aggregate, mastic, and air voids. The computed tomography (CT) image-based finite element approach is used as an effective method to simulate micromechanical response of asphalt mixture. For finite element analysis, the accuracy of the finite results is determined by the size of the finite element. In this paper, a voxel-based three-dimensional (3D) digital reconstruction model of asphalt mixture with the CT images after being processed was proposed. In this 3D model, the aggregate phase was considered as elastic materials while the asphalt mastic phase was considered as linear viscoelastic material. Four micromechanical digital models were generated, whose voxel sizes were 0.5 mm, 0.67 mm, 1.0 mm, and 2.0 mm, respectively. The four digital models were used to conduct uniaxial creep test for predicting creep stiffness modulus to investigate the effect of voxel size. Simulation results showed that the voxel sizes had a significant effect on creep stiffness modulus. For the creep simulation test, the most appropriate voxel size whose creep stiffness modulus changes within 2.5% is 1.0 mm with regard to time steps, computational time, aggregate, and mastic shape representations.
ISSN:1687-8434
1687-8442