.png){kind=icon}
返回
Line sampling-based local and global reliability sensitivity analysis
.png){kind=icon}
PRE
AI
DOI：10.1007/s00158-019-02358-9.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Local reliability sensitivity (RS) and global RS can provide useful information in reliability-based design optimization, but the algorithmfor solving them is still a challenge, especially in case of small failure probability and high dimensionality. In this paper, a novel method by combining Monte Carlo simulation (MCS) with line sampling (LS), an efficient method for estimating small failure probability in case of the high dimensionality, is proposed to evaluate local RS and global RS simultaneously. Since the proposed method employs LS samples to approximately screen out the failure samples from the MCS sample set, the proposed method possesses both the efficiency of the LS and the accuracy of the MCS. One numerical example and two engineering examples illustrate the accuracy and the efficiency of the proposed method.
Keyword:
Reliability
Local reliability sensitivity
Global reliability sensitivity
Line sampling
Monte Carlo simulation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4
论文数:
4.9K
被引数:
1.7W
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容