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.

中文翻译：

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具有凹形颗粒的土石混合体三维中尺度计算模型

摘要 土石混合体（SRMs）是西南地区主要的不利地质体。本文提出了一种新的中尺度计算建模研究，研究了具有凹形聚集体的 SRM。通过结合基于 Gilbert-Johnson-Keerthi (GJK) 的碰撞检测技术、边界放置算法和粒子位置选择方法，提出了一种高效的 3D 中尺度 SRM 生成方法。基于网格映射技术生成周期性网格。实现了具有大量元素的SRM的数值均匀化分析，并通过实验测试结果验证了估计的参数。结果表明，具有凹形聚集体的 SRM 比具有凸形聚集体的 SRM 具有更高的弹性模量。