A Framework for Validation of Computer Models

M.J. Bayarri, J.O. Berger, D. Higdon, M.C. Kennedy, A. Kottas, R. Paulo, J. Sacks, J.A. Cafeo, J. Cavendish, C.H. Lin, and J. Tu

In this paper, we present a framework that enables computer model evaluation oriented towards answering the question: Does the computer model adequately represent reality? The proposed validation framework is a six-step procedure based upon Bayesian statistical methodology. The Bayesian methodology is particularly suited to treating the major issues associated with the validation process: quantifying multiple sources of error and uncertainty in computer models; combining multiple sources of information; and updating validation assessments as new information is acquired. Moreover, it allows inferential statements to be made about predictive error associated with model predictions in untested situations.

The framework is implemented in two test bed models (a vehicle crash model and a resistance spot weld model) that provide context for each of the six steps in the proposed validation process.

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