Technical Papers
Nov 2, 2022

The GCO Method for Time-Dependent Structural Reliability Assessment

Publication: Journal of Engineering Mechanics
Volume 149, Issue 1

Abstract

By taking the advantage of Poisson events, the outcrossing method has been widely applied for time-dependent reliability analysis considering continuous processes. Generally, the outcrossing method can only obtain an upper bound of failure probability, which will overestimate the risk and result in unnecessary maintenance costs. In this study, a general conditional outcrossing (GCO) method for time-dependent reliability analysis was proposed, which can obtain a more accurate probability of failure. The conditional outcrossing rate was defined as the outcrossing rate conditioned on fixing the values of time-invariant random variables, which was introduced to satisfy the assumption of independent outcrossing events. A numerical algorithm for the GCO method was developed with the aid of the Gauss-Legendre quadrature and point estimate method. The application of the GCO method is demonstrated by three examples, including an implicit limit state function with a finite-element model and non-Gaussian nonstationary random processes. The failure probability obtained by the GCO method was found to be in close agreement with that by Monte Carlo simulation, which demonstrates the accuracy of the GCO method.

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Data Availability Statement

All data, models, and code used during the study are available from the corresponding author upon reasonable request.

Acknowledgments

The study is partially supported by the National Natural Science Foundation of China (Grant Nos. 52108104, 51820105014, 51738001, and U19342171) and the 111 Project (Grant No. D21001). The supports are gratefully acknowledged.

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Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 149Issue 1January 2023

History

Received: Jan 11, 2022
Accepted: Aug 27, 2022
Published online: Nov 2, 2022
Published in print: Jan 1, 2023
Discussion open until: Apr 2, 2023

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Xuan-Yi Zhang [email protected]
Associate Professor, Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing Univ. of Technology, No. 100 Pingleyuan, Beijing 100124, China. Email: [email protected]
Zhao-Hui Lu [email protected]
Professor, Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing Univ. of Technology, No. 100 Pingleyuan, Beijing 100124, China (corresponding author). Email: [email protected]
Yan-Gang Zhao, M.ASCE [email protected]
Professor, Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing Univ. of Technology, No. 100 Pingleyuan, Beijing 100124, China. Email: [email protected]

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