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Evidence-theory-based reliability design optimization with parametric correlations

  • Z. L. Huang
  • C. JiangEmail author
  • Z. Zhang
  • W. Zhang
  • T. G. Yang
Research Paper
  • 86 Downloads

Abstract

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.

Keywords

Parametric correlation Copula function Evidence theory Reliability optimal Decoupling approach 

Notes

Acknowledgements

Supported by the Major Program of National Natural Science Foundation of China (51490662), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (51621004), the National Science Fund for Distinguished Young Scholars (51725502), the Natural Science Foundation of Hunan Province of China (2017JJ2012), and the Educational Commission of Hunan Province of China (17A036).

Supplementary material

158_2019_2225_MOESM1_ESM.rar (63 kb)
ESM 1 (RAR 62 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mechanical and Electrical EngineeringHunan City UniversityYiyang CityPeople’s Republic of China
  2. 2.State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle EngineeringHunan UniversityChangsha CityPeople’s Republic of China
  3. 3.Science and Math ClusterSingapore University of Technology and DesignSingaporeSingapore

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