Abstract In this work, a data-driven reduced-order model is presented to predict the microscale spatial distribution of the plastic strain rate tensor in an isotropic two-phase composite subjected to an arbitrary macroscopically imposed strain rate tensor. This model was built using the framework of localization linkages called Material Knowledge Systems (MKS), which has been demonstrated to exhibit a remarkable combination of accuracy and low computational cost. In prior work, the MKS framework was successfully used to predict the local strain rate fields in multiphase composites subjected to a selected macroscale strain rate tensor. In this work, the MKS framework is extended to include the complete set of all macroscale strain rate tensors that could be applied. This is accomplished by developing novel representations that allow a parametrization of the localization kernel over the complete space of unit symmetric traceless second-rank tensors and implementing them with the required fast computational strategies. The MKS localization linkage produced in this work was calibrated and validated to results from microscale finite element models.

中文翻译：

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使用材料知识系统框架预测受任意宏观应变率影响的两相复合材料的微观塑性应变率场

摘要 在这项工作中，提出了一种数据驱动的降阶模型来预测受任意宏观施加应变率张量影响的各向同性两相复合材料中塑性应变率张量的微观空间分布。该模型是使用称为材料知识系统 (MKS) 的本地化链接框架构建的，该框架已被证明具有准确性和低计算成本的显着组合。在先前的工作中，MKS 框架被成功地用于预测多相复合材料中受选定宏观应变率张量影响的局部应变率场。在这项工作中，MKS 框架被扩展为包括可以应用的所有宏观应变率张量的完整集合。这是通过开发新颖的表示来实现的，这些表示允许在单位对称无迹二阶张量的完整空间上对定位内核进行参数化，并使用所需的快速计算策略实现它们。在这项工作中产生的 MKS 定位链接被校准和验证为来自微尺度有限元模型的结果。