The reliability based design optimization (RBDO) method is prevailing in stochastic structural design optimization by assuming the amount of input data is sufficient enough to create accurate input statistical distribution. If the sufficient input data cannot be generated due to limitations in technical and/or facility resources, the possibility-based design optimization (PBDO) method can be used to obtain reliable designs by utilizing membership functions for epistemic uncertainties. For RBDO, the performance measure approach (PMA) is well established and accepted by many investigators. It is found that the same PMA is a very much desirable approach also for the PBDO problems. In many industry design problems, we have to deal with uncertainties with sufficient data and uncertainties with insufficient data simultaneously. For these design problems, it is not desirable to use RBDO since it could lead to an unreliable optimum design. This paper proposes to use PBDO for design optimization for such problems. In order to treat uncertainties as fuzzy variables, several methods for membership function generation are proposed. As less detailed information is available for the input data, the membership function that provides more conservative optimum design should be selected. For uncertainties with sufficient data, the membership function that yields the least conservative optimum design is proposed by using the possibility-probability consistency theory and the least conservative condition. The proposed approach for design problems with mixed type input uncertainties is applied to some example problems to demonstrate feasibility of the approach. It is shown that the proposed approach provides conservative optimum design.
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e-mail: kkchoi@ccad.uiowa.edu
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July 2006
Research Papers
Possibility-Based Design Optimization Method for Design Problems With Both Statistical and Fuzzy Input Data
Liu Du,
Liu Du
Department of Mechanical & Industrial Engineering, College of Engineering,
The University of Iowa
, Iowa City, IA 52242
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K. K. Choi,
K. K. Choi
Department of Mechanical & Industrial Engineering, College of Engineering,
e-mail: kkchoi@ccad.uiowa.edu
The University of Iowa
, Iowa City, IA 52242
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Byeng D. Youn,
Byeng D. Youn
Department of Mechanical Engineering, College of Engineering,
University of Detroit Mercy
, Detroit, MI 48219
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David Gorsich
David Gorsich
AMSTA-TR-N (MS 263),
U.S. Army National Automotive Center
, Warren, MI 48397
Search for other works by this author on:
Liu Du
Department of Mechanical & Industrial Engineering, College of Engineering,
The University of Iowa
, Iowa City, IA 52242
K. K. Choi
Department of Mechanical & Industrial Engineering, College of Engineering,
The University of Iowa
, Iowa City, IA 52242e-mail: kkchoi@ccad.uiowa.edu
Byeng D. Youn
Department of Mechanical Engineering, College of Engineering,
University of Detroit Mercy
, Detroit, MI 48219
David Gorsich
AMSTA-TR-N (MS 263),
U.S. Army National Automotive Center
, Warren, MI 48397J. Mech. Des. Jul 2006, 128(4): 928-935 (8 pages)
Published Online: November 23, 2005
Article history
Received:
July 13, 2005
Revised:
November 23, 2005
Citation
Du, L., Choi, K. K., Youn, B. D., and Gorsich, D. (November 23, 2005). "Possibility-Based Design Optimization Method for Design Problems With Both Statistical and Fuzzy Input Data." ASME. J. Mech. Des. July 2006; 128(4): 928–935. https://doi.org/10.1115/1.2204972
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