A Case Study in Model Improvement For Vehicle Crashworthiness Simulation

摘要

This paper presents a case study of experimentally-based "model improvement" (also known as "model updating") for numerical simulations of vehicle crashworthiness testing. The paper details the steps involved the model updating process, including the detection, identification and correction of systematic modeling and/or experimental errors, parameter selection and subsequent Bayesian parameter estimation, and the statistical qualification of those estimates. While parameter estimation and qualification are straightforward computational procedures, the detection, identification and correction of systematic errors is not; it is fundamentally intuitive and requires the expertise and experience of both the modeler and experimentalist. This model updating effort was successful in identifying two systematic modeling deficiencies. The identification and correction of these deficiencies is expected to benefit future crashworthiness simulation efforts at GM.