Random Field Realization and Fracture Simulation of Rocks With Angular Bias for Fracture Strength
Random Field Realization and Fracture Simulation of Rocks With Angular Bias for Fracture Strength
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发表时间：
2018-08
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通讯作者：
J. Garrard;R. Abedi;P. Clarke
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作者：
J. Garrard;R. Abedi;P. Clarke
岩石作为一种具有显著内在随机性的非均质脆性材料，其真实的断裂模拟需要使用包含其非均质性和统计变异性的模型。由于断裂过程对微观组织缺陷的高度依赖，导致了极限强度的广泛分散和所谓的尺寸效应。提出了一种基于统计体积元(SVEs)的岩石细观断裂强度表征方法。SVE的使用确保了材料的随机性在平均微尺度特征时保持不变。由于断裂强度不仅在空间上变化，而且随着加载角度的不同而变化，这项工作包括角度可变性，以适当地模拟非均质岩石域。两种不同的微裂纹分布，一种是角度均匀的，另一种是倾斜到特定角度的，用来说明在随机场中加入角度可以提供最逼真的断裂模拟。采用自适应异步时空间断伽辽金(ASDG)有限元方法进行动态断裂模拟。致谢：作者感谢通过美国国家科学基金会(NSF)、CMMI材料与结构力学(MOMS)计划拨款1538332和CCF极限可伸缩并行(SPX)计划拨款1725555对这项工作的部分支持。
Realistic fracture simulations in rock as a heterogeneous brittle material with significant inherent randomness require the use of models that incorporate its inhomogeneities and statistical variability. The high dependence of their fracture progress on microstructural defects results in wide scatter in their ultimate strength and the so-called size effect. This paper proposes an approach based on statistical volume elements (SVEs) to characterize rock fracture strength at the mesoscale. The use of SVEs ensures that the material randomness is maintained upon averaging of microscale features. Because the fracture strength varies not just spatially, but also by the angle of loading, this work includes angular variability to properly model a heterogeneous rock domain. Two different microcrack distributions, one angularly uniform and one angularly biased towards a specific angle, are used to show that implementing angle into the random field provides the most realistic fracture simulation. An adaptive asynchronous spacetime discontinuous Galerkin (aSDG) finite element method is used to perform the dynamic fracture simulations. Acknowledgments: The authors gratefully acknowledge partial support for this work via the U.S. National Science Foundation (NSF), CMMI Mechanics of Materials and Structures (MoMS) program grant number 1538332 and CCF Scalable Parallelism in the Extreme (SPX) program grant number 1725555.