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Evidence-theory-based reliability design optimization with parametric correlations
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DOI：10.1007/s00158-019-02225-7.png)
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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.
Keyword:
Parametric correlation
Copula function
Evidence theory
Reliability optimal
Decoupling approach
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