线性系统在非高斯风激励下的首次穿越可靠性灵敏度分析：基于曲面分解方法

中文摘要 AI 辅助

本文提出了一种曲面分解方法，用于对承受非高斯风激励的线性系统进行首次穿越动态可靠性灵敏度分析。首次穿越失效概率灵敏度被表述为在一个高度非光滑且高维的超曲面上的系统曲面积分。该复杂积分首先被分解为一系列在截断的光滑二次超曲面上的分量曲面积分。然后，基于分量失效概率的一阶近似的相对大小，识别出主导分量。构建了一种嵌套采样算法来高效估计这些分量曲面积分之和，其中系统极限状态函数的评估次数等于外层样本数，而与内层样本量无关。本方法的一个关键优势是，函数评估结果可以在不同设计参数之间重复使用。通过两个数值算例验证了所提方法的有效性。结果表明，要达到目标变异系数0.1，所需的函数评估次数通常低于100次。

英文摘要

This contribution develops a surface decomposition method for first-passage dynamic reliability sensitivity analysis of linear systems exposed to non-Gaussian wind excitations. The first-passage failure probability sensitivity is formulated as a system surface integral over a highly non-smooth and high-dimensional hypersurface. This complex integral is first decomposed into a collection of component surface integrals over the truncated smooth quadratic hypersurfaces. The dominant components are then identified based on the relative magnitudes of the first-order approximations of the component failure probabilities. A nested sampling algorithm is constructed to efficiently estimate the sum of these component surface integrals, in which the number of system limit-state function evaluations equals the number of outer-level samples while remaining independent of the inner-level sample size. A key advantage of the present approach is that the function evaluation results can be reused across different design parameters. Two numerical examples are explored to demonstrate the effectiveness of the proposed method. The results indicate that the number of function evaluations required is typically below 100 to achieve a target coefficient of variation of 0.1.

发表机构

• South China University of Technology（华南理工大学）
• The University of Hong Kong（香港大学）
• Guangzhou City University of Technology（广州城市理工学院）

机构由 AI 辅助整理，请以论文原文为准。