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Structural and Multidisciplinary Optimization
Erschienen in: Structural and Multidisciplinary Optimization 2/2019

13.03.2019 | Research Paper

Evidence-theory-based reliability design optimization with parametric correlations

verfasst von: Z. L. Huang, C. Jiang, Z. Zhang, W. Zhang, T. G. Yang

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 2/2019

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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.
Vorheriger Artikel A simulated annealing approach for optimizing composite structures blended with multiple stacking sequence tables
Nächster Artikel A novel global optimization algorithm and data-mining methods for turbomachinery design

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Metadaten
Titel
Evidence-theory-based reliability design optimization with parametric correlations
verfasst von
Z. L. Huang
C. Jiang
Z. Zhang
W. Zhang
T. G. Yang
Publikationsdatum
13.03.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 2/2019
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-019-02225-7

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