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：晶体塑性有限元模型作为集成计算材料工程工具箱中强有力的数值模拟工具，能够在计算材料科学中建立微观结构与均匀化材料性能的关联，并构建结构-性能关系。然而，为建立预测能力，需校准底层本构模型、验证求解方案，并通过实验数据确认模型预测的准确性。贝叶斯优化作为一种免梯度的高效全局优化算法，已成功应用于晶体塑性有限元本构模型的校准。本文采用最新开发的异步并行约束贝叶斯优化算法，对304L不锈钢、钽及康托尔高熵合金的唯象本构模型进行校准。