Presented at 41st AIAA Conf. Aerospace Sciences (Paper Number 2003-0630), January 7, 2003, Reno

Uncertainty quantification of simulation codes based on experimental data

Kenneth M. Hanson and François M. Hemez
Los Alamos National Laboratory


We present an approach for assessing the uncertainties in simulation code outputs in which one focuses on the physics submodels incorporated into the code. Through a Bayesian analysis of a hierarchy of experiments that explore various aspects of the physics submodels, one can infer the sources of uncertainty, and quantify them. As an example of this approach, we describe an effort to describe the plastic-flow characteristics of a high-strength steel by combining data from basic material tests with an analysis of Taylor impact experiments. A thorough analysis of the material-characterization experiments is described, which necessarily includes the systematic uncertainties that arise form sample-to sample variations in the plastic behaviour of the specimens. The Taylor experiments can only be understood by means of a simulation code. We describe how this analysis can be done and how the results can be combined with the results of analyses of data from simpler materialcharacterization experiments.

Keywords: simulation uncertainty, Monte Carlo technique, material-characterization experiments, Taylor cylinder impact test, model inference, likelihood analysis, systematic uncertainty, uncertainty assessment, probabilistic network, hierarchy of experiments, simulation code validation

Viewgraphs for this paper (pdf, 532 KB)
Send e-mail to author at