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