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Model Uncertainty Approximation Using a Copula-Based Approach for Reliability Based Design Optimization

[+] Author Affiliations
Hao Pan, Zhimin Xi

University of Michigan - Dearborn, Dearborn, MI

Ren-Jye Yang

Ford Motor Company, Dearborn, MI

Paper No. DETC2016-60071, pp. V01AT02A026; 11 pages
doi:10.1115/DETC2016-60071
From:
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1A: 36th Computers and Information in Engineering Conference
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5007-7
  • Copyright © 2016 by ASME

abstract

Reliability-based design optimization (RBDO) has been widely used to design engineering products with minimum cost function while meeting defined reliability constraints. Although uncertainties, such as aleatory uncertainty and epistemic uncertainty, have been well considered in RBDO, they are mainly considered for model input parameters. Model uncertainty, i.e., the uncertainty of model bias which indicates the inherent model inadequacy for representing the real physical system, is typically overlooked in RBDO. This paper addresses model uncertainty characterization in a defined product design space and further integrates the model uncertainty into RBDO. In particular, a copula-based bias correction approach is proposed and results are demonstrated by two vehicle design case studies.

Copyright © 2016 by ASME

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