Rigorous Uncertainty Quantification and Design with Uncertain Material Models
We assess a method of quantification of margins and uncertainties (QMU) in applications where the main source of uncertainty is an imperfect knowledge or characterization of the material behavior. The aim of QMU is to determine adequate design margins given quantified uncertainties and a desired level of confidence in the design. We quantify uncertainties through rigorous probability bounds computed by exercising an existing deterministic code in order to sample the mean response and identify worst-case combinations of parameters. The resulting methodology is non-intrusive and can be wrapped around existing solvers. The use of rigorous probability bounds ensures that the resulting designs are conservative to within a desired level of confidence. We assess the QMU framework by means of an application concerned with sub-ballistic impact of AZ31B Mg alloy plates. We assume the design specification to be a maximum allowable backface deflection of the plate. As a simple scenario, we specifically assume that, under the conditions of interest, the plate is well-characterized by the Johnson-Cook model, but the parameters of the model are uncertain. In calculations, we use the commercial finite-element package LS-Dyna and DAKOTA Version 6.7. The assessment demonstrates the feasibility of the approach and how it results in high-confidence designs that are well-within the practical range of engineering application.
© 2019 Elsevier Ltd. Received 21 July 2019, Revised 9 September 2019, Accepted 21 October 2019, Available online 25 October 2019.