Three-dimensional mesoscale computational modeling of soil-rock mixtures with concave particles

By Q. Meng, Huanling Wang, Ming Cai, Wei-ya Xu, Xiaoying Zhuang, Timon Rabczuk. 2020

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Abstract 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.

Subfields: Computational Mechanics, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/95797987e251b826e84a77392fc9016d6056656e