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Enhanced Sequential Optimization and Reliability Assessment Method for Changing Design Variance

[+] Author Affiliations
Xiaolei Yin, Wei Chen

Northwestern University, Evanston, IL

Paper No. DETC2005-84891, pp. 1163-1172; 10 pages
doi:10.1115/DETC2005-84891
From:
  • ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 31st Design Automation Conference, Parts A and B
  • Long Beach, California, USA, September 24–28, 2005
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4739-X | eISBN: 0-7918-3766-1
  • Copyright © 2005 by ASME

abstract

The Sequential Optimization and Reliability Assessment (SORA) method is a single loop method containing a sequence of cycles of decoupled deterministic optimization and reliability assessment for improving the efficiency of probabilistic optimization. However, the original SORA method as well as some other existing single loop methods is not efficient for solving problems with changing variance. In this paper, to enhance the SORA method, three formulations are proposed by taking the effect of changing variance into account. These formulations are distinguished by the different strategies of Inverse Most Probable Point (IMPP) approximation. Mathematical examples and a pressure vessel design problem are used to test and compare the effectiveness of the proposed formulations. The “Direct Linear Estimation Formulation” is shown to be the most effective and efficient approach for dealing with problems with changing variance. The gained insight can be extended and utilized to other optimization strategies that require MPP or IMPP estimations.

Copyright © 2005 by ASME

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