First-passage reliability sensitivity analysis of linear systems subjected to non-Gaussian wind excitations by surface decomposition method
Abstract
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.
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BibTeX
@misc{xian2026firstpassage,
title = {{First-passage reliability sensitivity analysis of linear systems subjected to non-Gaussian wind excitations by surface decomposition method}},
author = {Jianhua Xian and Sai Hung Cheung and Cheng Su},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.13799},
eprint = {2609.13799},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.13799},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - First-passage reliability sensitivity analysis of linear systems subjected to non-Gaussian wind excitations by surface decomposition method
AU - Jianhua Xian
AU - Sai Hung Cheung
AU - Cheng Su
PY - 2026
DA - 2026/09/12
PB - arXiv
DO - 10.48550/arxiv.2609.13799
UR - https://arxiv.org/abs/2609.13799
AB - 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.
ER -