Regional importance effect analysis of the input variables on failure probability

被引：11
|
作者：
Li, Luyi [1 ]
Lu, Zhenzhou [1 ]
机构：
[1] Northwestern Polytech Univ, Sch Aeronaut, Xian 710072, Peoples R China
来源：
COMPUTERS & STRUCTURES | 2013年 / 125卷
基金：
中国国家自然科学基金;
关键词：
Input variables; Regional importance; Failure probability; Adaptive radial-based importance sampling; INDEPENDENT IMPORTANCE MEASURE; SENSITIVITY-ANALYSIS; UNCERTAINTY IMPORTANCE;
D O I：
10.1016/j.compstruc.2013.04.026
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
To analyze the effects of the different regions within input variables on failure probability, a regional importance measure (RIM) is proposed, and its properties are analyzed and verified. The proposed RIM can not only detect the important variables, but also identify regions of the input variable that contribute substantially to the failure probability. To calculate the RIM efficiently, its calculation model is transformed, and the highly efficient adaptive radial-based importance sampling (ARBIS) method is introduced. Numerical and engineering examples have demonstrated the effectiveness of the proposed RIM, and the efficiency and accuracy of the established ARBIS method. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码：74 / 85
页数：12
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