Uncertainty Quantification in the Mechanical Response of Crystal Plasticity Simulations

Due to the uncertainty in calibrating the crystal plasticity (CP) model parameters, the present study quantifies the associated variability in the resulting mechanical response via a two-step process. First, a genetic algorithm framework is used to obtain the statistical distributions for the appropriate CP parameters. Second, those distributions are used in a first-order, second-moment method to compute the mean and the standard deviation for the stress along the loading direction (sigma(load)), plastic strain accumulation (PSA), and accumulated plastic strain energy density (W-p). The results suggest that a similar to 10% variability in sigma(load) and 20-25% variability in the PSA and W-p values may exist due to the uncertainty in the CP parameter estimation. Further, the contribution of a specific CP parameter to the overall uncertainty is path-dependent and varies based on the load step under consideration. The results of the present research will help practitioners to (1) identify the critical CP parameter(s) for a particular quantitative prediction of the mechanical response, (2) select appropriate experimental dataset(s) to calibrate the CP parameters, and (3) provide approximate variability in the crystal plasticity results which can propagate within a broader modeling framework.