ARC Collaborative Research Seminar Series Winter 2006
نویسندگان
چکیده
In the first part of this presentation, recent advances in reliability-based robust design optimization (RBRDO) will be presented. The objective of RBRDO is to minimize the product quality loss function subject to probabilistic constraints. Since the quality loss function is usually expressed in terms of the first two statistical moments, mean and variance, many methods have been proposed to accurately and efficiently estimate the moments. Among the methods, univariate dimension reduction method (DRM), performance moment integration (PMI), and percentile difference method (PDM) are recently proposed methods. In the presented work, estimation of statistical moments and their sensitivities are carried out using DRM and compared with results obtained using PMI and PDM. In addition, PMI and DRM are also compared in terms of how accurately and efficiently they estimate the statistical moments and their sensitivities of a performance function. In this comparison, PDM is excluded since PDM could not even accurately estimate the statistical moments of the performance function. Also, robust design optimization using DRM, PMI, and PDM are carried out and the results are compared. Several numerical examples are used for the two comparisons. The comparisons show that DRM is effective when the number of design variables is small and PMI is effective when the number of design variables is relatively large. For the inverse reliability analysis of reliability-based design, the enriched performance measure approach (PMA+) is used.
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