Crystal plasticity finite element model (CPFEM) is a powerful numerical simulation in the integrated computational materials engineering (ICME) toolboxes that relates microstructures to homogenized materials properties and establishes the structure-property linkages in computational materials science. However, to establish the predictive capability, one needs to calibrate the underlying constitutive model, verify the solution and validate the model prediction against experimental data. Bayesian optimization (BO) has stood out as a gradient-free efficient global optimization algorithm that is capable of calibrating constitutive models for CPFEM. In this paper, we apply a recently developed asynchronous parallel constrained BO algorithm to calibrate phenomenological constitutive models for stainless steel 304L, Tantalum, and Cantor high-entropy alloy.

翻译：晶体塑性有限元本构模型的异步并行高吞吐量模型校准框架 翻译后的摘要： 晶体塑性有限元模型（CPFEM）是计算材料科学中集成计算材料工程（ICME）工具箱中的强大数值模拟工具，能够将微观结构与均质材料属性联系起来，在计算材料科学中建立结构 - 属性关联。然而，为了建立预测能力，需要校准底层本构模型，验证解决方案并基于实验数据验证模型预测。贝叶斯优化（BO）作为一种无梯度高效全局优化算法，已成为对CPFEM本构模型进行校准的最佳选择。本文采用最近开发的异步并行受约束BO算法来校准不同材料的不同本构模型，包括不锈钢304L，钽和Cantor高熵合金。