Reliability Sensitivity Algorithm Based on Stratified Importance Sampling Method for Multiple Failure Modes Systems  

作　　者：Zhang Feng Lu Zhenzhou Cui Lijie Song Shufang 

机构地区：[1]School of Mechanics and Civil and Architecture, Northwestern Polytechnical University, Xi 'an 710072, China [2]School of Aeronautics, Northwestern Polyteehnical University. Xi 'an 710072, China

出　　处：《Chinese Journal of Aeronautics》2010年第6期660-669,共10页中国航空学报（英文版）

基　　金：National Natural Science Foundation of China (10572117,10802063,50875213);Aeronautical Science Foundation of China (2007ZA53012);New Century Program For Excellent Talents of Ministry of Education of China (NCET-05-0868);National High-tech Research and Development Program (2007AA04Z401)

摘　　要：Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.

关 键 词：multiple failure modes reliability sensitivity Monte Carlo simulation stratified sampling method importance sam-piing method stratified importance sampling method （SISM） 

分 类 号：O346.1[理学—固体力学] U463.01[理学—力学]