...
首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Adaptive selection of reference stiffness in virtual clustering analysis
【24h】

Adaptive selection of reference stiffness in virtual clustering analysis

机译:虚拟聚类分析中的参考刚度的自适应选择

获取原文
获取原文并翻译 | 示例
           

摘要

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. (C) 2020 Elsevier B.V. All rights reserved.
机译:已经开发了虚拟聚类分析(VCA)以用于异质材料的数值均匀化。材料系统的整体形式是Lippmann-Schwinger方程,其在无限远处施加边界条件,用于围绕均匀的均匀参考材料。人工选择的参考刚度引起了材料边界上的牵引的分布。均匀加载牵引边界条件的偏差降低了预测所考虑的材料的平均刚度的精度。在这项工作中,我们建议诱导的牵引力应在一个标准偏差范围内,并提出了一种更新参考刚度的自适应策略。用弹性塑性组成夹杂物问题的数值试验验证了拟议策略的有效性。 (c)2020 Elsevier B.v.保留所有权利。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号