  The advent of fabrication techniques such as additive manufacturing has
focused attention on the considerable variability of material response due to
defects and other microstructural 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.
