Efficient approach for reliability-based optimization based on weighted importance sampling approach

被引:34
|
作者
Yuan, Xiukai [1 ]
Lu, Zhenzhou [2 ]
机构
[1] Xiamen Univ, Dept Aeronaut, Xiamen 361005, Peoples R China
[2] Northwestern Polytech Univ, Sch Aeronaut, Xian 710072, Peoples R China
基金
中国国家自然科学基金;
关键词
Reliability-based optimization; Decoupling; Importance sampling; Monte Carlo simulation; DYNAMICAL-SYSTEMS; DESIGN; SENSITIVITY;
D O I
10.1016/j.ress.2014.06.015
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:107 / 114
页数:8
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