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Crystal plasticity finite element model (CPFEM) is a powerful numericalsimulation in the integrated computational materials engineering (ICME)toolboxes that relates microstructures to homogenized materials properties andestablishes the structure-property linkages in computational materials science.However, to establish the predictive capability, one needs to calibrate theunderlying constitutive model, verify the solution and validate the modelprediction against experimental data. Bayesian optimization (BO) has stood outas a gradient-free efficient global optimization algorithm that is capable ofcalibrating constitutive models for CPFEM. In this paper, we apply a recentlydeveloped asynchronous parallel constrained BO algorithm to calibratephenomenological constitutive models for stainless steel 304L, Tantalum, andCantor high-entropy alloy.

An asynchronous parallel high-throughput model calibration framework for crystal plasticity finite element constitutive models