Some metrics and a Bayesian procedure for validating predictive models in engineering design

Wei Chen*, Ying Xiong, Kwok Leung Tsui, Shuchun Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

Even though model-based simulations are widely used in engineering design, it remains a challenge to validate models and assess the risks and uncertainties associated with the use of predictive models for design decision making. In most of the existing work, model validation is viewed as verifying the model accuracy, measured by the agreement between computational and experimental results. However, from the design perspective, a good model is considered as the one that can provide the discrimination (good resolution) between design candidates. In this work, a Bayesian approach is presented to assess the uncertainty in model prediction by combining data from both physical experiments and the computer model. Based on the uncertainty quantification of model prediction, some design-oriented model validation metrics are further developed to guide designers for achieving high confidence of using predictive models in making a specific design decision. We demonstrate that the Bayesian approach provides a flexible framework for drawing inferences for predictions in the intended but may be untested design domain, where design settings of physical experiments and the computer model may or may not overlap. The implications of the proposed validation metrics are studied, and their potential roles in a model validation procedure are highlighted.

Original languageEnglish (US)
Title of host publicationProceedings of 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006
StatePublished - Nov 29 2006
Event2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006 - Philadelphia, PA, United States
Duration: Sep 10 2006Sep 13 2006

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume2006

Other

Other2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006
CountryUnited States
CityPhiladelphia, PA
Period9/10/069/13/06

Keywords

  • Bayesian approach
  • Design
  • Model validation
  • Predictive modeling
  • Uncertainty quantification
  • Validation metrics

ASJC Scopus subject areas

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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