Evidence-theory-based reliability design optimization with parametric correlations

被引：0
|
作者：
Z. L. Huang
C. Jiang
Z. Zhang
W. Zhang
T. G. Yang
机构：
[1] Hunan City University,School of Mechanical and Electrical Engineering
[2] Hunan University,State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering
[3] Singapore University of Technology and Design,Science and Math Cluster
来源：
Structural and Multidisciplinary Optimization | 2019年 / 60卷
关键词：
Parametric correlation; Copula function; Evidence theory; Reliability optimal; Decoupling approach;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Parametric correlation exists widely in engineering problems. This paper presents an approach of evidence-theory-based design optimization (EBDO) with parametric correlations, which provides an effective computational tool for the structural reliability design involving epistemic uncertainties. According to the existing samples, the most fitting copula function is selected to formulate the joint basic probability assignment (BPA) of the correlated variables. The joint BPA is applied in the constraint reliability analysis, and an approximate technology is given to enhance the efficiency. A decoupling strategy is proposed for transforming the nested optimization of EBDO into a sequential iterative process of deterministic optimization and reliability analysis. The effectiveness of the proposed approach is demonstrated through two numerical examples and an engineering application.
引用
收藏
页码：565 / 580
页数：15
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