汽车工程 ›› 2023, Vol. 45 ›› Issue (6): 1081-1089.doi: 10.19562/j.chinasae.qcgc.2023.06.018

所属专题: 车身设计&轻量化&安全专题2023年

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矢量-角度几何映射的方向重要抽样分布函数近似化方法及多失效模式可靠性分析

王俊峰1,2,陈吉清1,2,兰凤崇1,2(),刘青山1,2   

  1. 1.华南理工大学机械与汽车工程学院,广州  510640
    2.华南理工大学,广东省汽车工程重点实验室,广州 510640
  • 修回日期:2023-02-08 出版日期:2023-06-25 发布日期:2023-06-16
  • 通讯作者: 兰凤崇 E-mail:fclan@scut.edu.cn
  • 基金资助:
    国家自然科学基金(52175267);广州市科技计划项目(202007020007);广东省自然科学基金(2021A15150912)

Approximation Method of Distribution Function Based on Directional Importance Sampling of Vector-Angle Geometric Mapping and Reliability Analysis of Multiple Failure Modes

Junfeng Wang1,2,Jiqing Chen1,2,Fengchong Lan1,2(),Qingshan Liu1,2   

  1. 1.School of Mechanical & Automotive Engineering,South China University of Technology,Guangzhou 510640
    2.Guangdong Province Key Laboratory of Vehicle Engineering,South China University of Technology,Guangzhou 510640
  • Revised:2023-02-08 Online:2023-06-25 Published:2023-06-16
  • Contact: Fengchong Lan E-mail:fclan@scut.edu.cn

摘要:

方向重要抽样法是一种结构可靠度模拟方法,适合评估非线性、多维度的复杂结构可靠性问题。然而对于多维度问题,利用接受/拒绝方法获得重要矢量样本,效率较低且可执行性差。因此,需要改进或重新构造易于抽样的分布函数。通过概述现有的分布函数,利用插值方法近似构造基于矢量-角度几何映射的分布函数,利用一维拉丁超立方方法对重要角度均匀抽样,再映射到重要矢量样本,得到的矢量样本具有分层均匀性,避免了聚集现象,同时覆盖整个样本空间。该方法有效应用于多设计点和多失效模式的可靠性问题分析中,进一步制定了样本分配方案。通过非线性数值算例和车身结构工程问题验证了该方法的适用性和准确性。

关键词: 可靠性分析, 方向重要抽样, 分布函数, 插值, 多失效模式, 样本分配

Abstract:

The directional importance sampling method is a structural reliability simulation method, which is suitable for evaluating nonlinear, multi-dimensional complex structural reliability problems. However, for multidimensional problems, it is relatively inefficient and poorly executable to obtain significant vector samples using the accept/reject method. Therefore, it is necessary to improve or reconstruct distribution functions that are easy to sample. By summarizing the existing distribution functions, the distribution function based on vector-angle geometric mapping is approximated by interpolation methods, and the important angles are sampled uniformly using the one-dimensional Latin hypercube method and then mapped to the important vector samples. The obtained vector samples have stratified uniformity, avoiding aggregation phenomena while covering the entire sample space. The method is effectively used in the analysis of reliability problems of multiple design points and multiple failure modes, and sample allocation scheme is further developed. The applicability and accuracy of the proposed method are verified by nonlinear numerical examples and body structure engineering.

Key words: reliability analysis, directional importance sampling, distribution function, interpolation, multiple failure modes, sample allocation