Yuan, Xiukai, Liu, Shaolong, Valdebenito, MA, Gu, Jian and Beer, Michael 
ORCID: 0000-0002-0611-0345
(2021)
Efficient procedure for failure probability function estimation in augmented space.
Structural Safety, 92.
p. 102104.
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Manuscript_XYuan_20210423 (STRUCS) .pdf - Author Accepted Manuscript Download (1MB) | Preview |
Abstract
An efficient procedure is proposed to estimate the failure probability function (FPF) with respect to design variables, which correspond to distribution parameters of basic structural random variables. The proposed procedure is based on the concept of an augmented reliability problem, which assumes the design variables as uncertain by assigning a prior distribution, transforming the FPF into an expression that includes the posterior distribution of those design variables. The novel contribution of this work consists of expressing this target posterior distribution as an integral, allowing it to be estimated by means of sampling, and no distribution fitting is needed, leading to an efficient estimation of FPF. The proposed procedure is implemented within three different simulation strategies: Monte Carlo simulation, importance sampling and subset simulation; for each of these cases, expressions for the coefficient of variation of the FPF estimate are derived. Numerical examples illustrate performance of the proposed approaches.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Failure probability function, Bayesian theory, Reliability analysis, Reliability-based optimization |
| Divisions: | Faculty of Science and Engineering > School of Engineering |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 15 Jun 2021 07:33 |
| Last Modified: | 18 Jan 2023 22:34 |
| DOI: | 10.1016/j.strusafe.2021.102104 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3126405 |
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