An Experimental, Computational, and Statistical Strategy for the Bayesian Calibration of Complex Material Models

Abstract The study of solids and structures under extreme conditions often relies on simulations that employ complex material models. These, in turn, are formulated using analytical expressions depend parameters whose values need to be adjusted for optimally reproducing available experimental results and, especially, out-of-sample predictiveness. In this article we review the process required calibrate all Johnson-Cook Zerilli-Armstrong models a nickel-based superalloy. To end, present an unified fashion thermomechanical problem, its numerical implementation, complete campaign suffices obtain constants, Bayesian calibration procedure can employed optimal model as well their uncertainty. advocated methodology is ideally designed strain rate-, temperature-, age-dependent elastoplastic is, however, general enough guideline other calibrations.