  The advent of fabrication techniques like additive manufacturing has focused
attention on the considerable variability of material response due to defects
and other micro-structural aspects. This variability motivates the development
of an enhanced design methodology that incorporates inherent material
variability to provide robust predictions of performance. In this work, we
develop plasticity models capable of representing the distribution of
mechanical responses observed in experiments using traditional plasticity
models of the mean response and recently developed uncertainty quantification
(UQ) techniques. We demonstrate that the new method provides predictive
realizations that are superior to more traditional ones, and how these UQ
techniques can be used in model selection and assessing the quality of
calibrated physical parameters.
