Dimension reduction method for reliability-based robust design optimization

Authors:
Ikjin Lee;K. K. Choi;Liu Du;David Gorsich
Affiliations:
Department of Mechanical and Industrial Engineering, College of Engineering, The University of Iowa, Iowa City, IA 52241, United States;Department of Mechanical and Industrial Engineering, College of Engineering, The University of Iowa, Iowa City, IA 52241, United States;Department of Mechanical and Industrial Engineering, College of Engineering, The University of Iowa, Iowa City, IA 52241, United States;US Army RDECOM/TARDEC AMSRD-TAR-N, MS 157, 6501 East 11 Mile Road, Warren, MI 48397-5000, United States
Venue:
Computers and Structures
Year:
2008

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Abstract

In reliability-based robust design optimization (RBRDO) formulation, the product quality loss function is minimized subject to probabilistic constraints. Since the quality loss function is expressed in terms of the first two statistical moments, mean and variance, three methods have been recently proposed to accurately and efficiently estimate the moments: the univariate dimension reduction method (DRM), performance moment integration (PMI) method, and percentile difference method (PDM). In this paper, a reliability-based robust design optimization method is developed using DRM and compared to PMI and PDM for accuracy and efficiency. The numerical results show that DRM is effective when the number of random variables is small, whereas PMI is more effective when the number of random variables is relatively large.