期刊
ENGINEERING GEOLOGY
卷 277, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.enggeo.2020.105802
关键词
3D mesoscale modeling; Soil and rock mixture; Numerical homogenization; Concave particles
资金
- National Key R&D Program of China [2018YFC0407004]
- Fundamental Research Funds for the Central Universities [B200201059]
- National Natural Science Foundation of China [51709089, 51609070, 11572110, 51479049, 11771116]
- China Postdoctoral Science Foundation [2018T110434]
- 111 project
Soil-rock mixtures (SRMs) are the main unfavorable geologic bodies in Southwest China. This paper presents a novel mesoscale computational modeling study of SRMs with concave aggregates. An efficient 3D mesoscale SRM generation method is proposed by combining the Gilbert-Johnson-Keerthi (GJK)-based collision detection technique, the border placement algorithm and the particle position selection method. A periodic mesh is generated based on the mesh mapping technique. A numerical homogenization analysis of an SRM with a large number of elements is realized, and the estimated parameters are validated by the experimental test results. The results indicate that SRMs with concave aggregates have a higher elastic modulus than those with convex aggregates. This method is helpful for predicting the physical properties of SRMs and has promising applications in engineering.
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