期刊
RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 132, 期 -, 页码 107-114出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2014.06.015
关键词
Reliability-based optimization; Decoupling; Importance sampling; Monte Carlo simulation
资金
- National Natural Science Foundation of China [51105309, 51175425]
An efficient methodology is presented to perform the reliability-based optimization (RBO). It is based on an efficient weighted approach for constructing an approximation of the failure probability as an explicit function of the design variables which is referred to as the 'failure probability function (FPF)'. It expresses the FPF as a weighted sum of sample values obtained in the simulation-based reliability analysis. The required computational effort for decoupling in each iteration is just single reliability analysis. After the approximation of the FPF is established, the target RBO problem can be decoupled into a deterministic one. Meanwhile, the proposed weighted approach is combined with a decoupling approach and a sequential approximate optimization framework. Engineering examples are given to demonstrate the efficiency and accuracy of the presented methodology. (C) 2014 Elsevier Ltd. All rights reserved.
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