航空学报 > 2018, Vol. 39 Issue (2): 221570-221570   doi: 10.7527/S1000-6893.2017.221570

基于交叉熵和空间分割的全局可靠性灵敏度分析

赵翔, 李洪双   

  1. 南京航空航天大学 航空宇航学院, 南京 210016
  • 收稿日期:2017-07-01 修回日期:2017-09-08 出版日期:2018-02-15 发布日期:2017-09-08
  • 通讯作者: 李洪双,E-mail:154552879@qq.com E-mail:hongshuangli@nuaa.edu.cn
  • 基金资助:
    国家自然科学基金(U1533109);南京航空航天大学研究生创新基地(实验室)开放基金(kfjj20160113)

Global reliability sensitivity analysis using cross entropy method and space partition

ZHAO Xiang, LI Hongshuang   

  1. College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2017-07-01 Revised:2017-09-08 Online:2018-02-15 Published:2017-09-08
  • Supported by:
    National Natural Science Foundation of China (U1533109);Foundation of Graduate Innovation Center in NUAA (kfjj20160113)

摘要: 基于失效概率的全局灵敏度分析可以度量各个基本随机变量的不确定性对失效概率的影响程度,对如何降低结构的失效概率具有指导意义。基于交叉熵方法和空间分割提出一种新全局可靠性灵敏度分析方法。该方法采用交叉熵法自适应的确定重要抽样密度函数,有效地回避了传统重要抽样中设计点位置和个数求解的困难。基于评估失效概率所使用的样本,利用空间分割方法计算各个输入随机变量的全局可靠性灵敏度指标,能够提高样本的利用率和计算效率。文中利用一个数值算例和两个工程算例验证了所提方法的计算效率和精度。

关键词: 全局可靠性灵敏度, 失效概率, 交叉熵方法, 空间分割, 重要抽样法

Abstract: Failure-probability-based sensitivity analysis is capable to measure the effects of uncertainties of input variables on failure probability, and can provide guidance on how to reduce the failure probability of a structure. In this paper, a new method is proposed to estimate the global reliability sensitivity indices, based on cross entropy method and space partition. The proposed method adaptively determines the important sampling density function by cross entropy method, avoiding the issue of determining the positions and number of the design points. Based on the identical set of samples used to estimate failure probability, the global reliability sensitivity index of each input random variable is calculated by the space partition method, which significantly improves the utilization of the samples and computational efficiency. A numerical and two engineering examples are used to illustrate the accuracy and efficiency of the proposed method.

Key words: global reliability sensitivity, failure probability, cross entropy method, sample space partition, importance sampling

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