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Adaptive selection of reference stiffness in virtual clustering analysis
Computer Methods in Applied Mechanics and Engineering ( IF 7.2 ) Pub Date : 2021-01-11 , DOI: 10.1016/j.cma.2020.113621
Xi Zhu , Lei Zhang , Shaoqiang Tang

Virtual clustering analysis (VCA) has been developed for numerical homogenization of heterogeneous material. The integral form of the material system is the Lippmann–Schwinger equation, which imposes boundary condition at infinity for fictitious surrounding homogeneous reference material. The artificially chosen reference stiffness induces a distribution for traction on the material boundary. The deviation from a uniform loading traction boundary condition degrades the accuracy in predicting the average stiffness of the material under consideration. In this work, we suggest that the induced traction should be within one standard deviation from the loading traction, and propose an adaptive strategy to update the reference stiffness. Numerical tests for inclusion problems with elasto-plasticity compositions verify the effectiveness of the proposed strategy.



中文翻译:

虚拟聚类分析中参考刚度的自适应选择

虚拟聚类分析(VCA)已开发用于异质材料的数值均质化。材料系统的整体形式是Lippmann-Schwinger方程,该方程对虚拟的周围均匀参考材料施加无穷大的边界条件。人工选择的参考刚度会在材料边界上产生牵引力分布。偏离均匀载荷牵引边界条件会降低预测所考虑材料的平均刚度的准确性。在这项工作中,我们建议感应牵引力应在距负载牵引力一个标准偏差之内,并提出一种自适应策略来更新参考刚度。

更新日期:2021-01-11
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