Presented at Statistical Sciences Seminar, April 28, 2003, Los Alamos National Laboratory

Material model inference from experimental data

Kenneth M. Hanson
Los Alamos National Laboratory


I will present a detailed description of the analysis of quasi-static and Hopkinson bar data for a high-strength steel, HSLA 100. The purpose of the analysis is to determine the parameters for a Zerilli-Armstrong model that are suitable for a room-temperature, high strain-rate application. Furthermore, a thorough uncertainty analysis is required to be able to predict the uncertainties in simulations of the application scenario. This example may appear to be just a straightforward data-fitting problem, albeit a nonlinear one. On the other hand, because of disagreement between the data and the Z-A model, a number of decisions need to be made. Part of the solution to obtaining an acceptable result is to introduce systematic uncertainties to account for sample-to-sample variations in behavior. My purpose in presenting this material is to induce an open discussion of the various ways to cope with and estimate the uncertainties.

Keywords: material model, inference, Zerilli-Armstrong model, systematic uncertainty, bias uncertainty, chi-squared, model fitting, uncertainty quantification, Bayesian analysis, material characterization experiments, HSLA 100 steel

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