Zhang, Yang, Xu, Jun and Beer, Michael 
ORCID: 0000-0002-0611-0345
(2023)
A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction.
Reliability Engineering & System Safety, 232.
p. 109031.
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Abstract
In this paper, a single-loop approach for time-variant reliability evaluation is proposed based on a decoupling strategy and probability distribution reconstruction. The most attractive feature of the proposed method is that the reliability at a specified time instant can be captured by performing time-invariant reliability analysis only once. In this method, the expansion optimal linear estimation is first employed to discretize the loading stochastic process. Then, a decoupling strategy that decouples the loading stochastic process and degradation processes is developed to formulate a single-loop method for time-variant reliability analysis, where an equivalent extreme value limit state function (EEV-LSF) is obtained. To improve the accuracy and robustness, the Box–Cox transformation is applied to get a transformed EEV-LSF. The maximum entropy method with fractional exponential moments is employed to robustly derive the probability distribution of transformed EEV-LSF. Once the probability distribution is captured, the time-variant failure probability can be readily computed. To handle a large number of random variables, a weighted sampling method is applied for moment assessment to ensure an efficient solution. Numerical examples including a complex real-world case are studied to validate the proposed method, where pertinent Monte Carlo simulations and PHI2 method are conducted for comparisons.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Time-variant reliability, Decoupling strategy, Box-Cox transformation, Fractional exponential moments, Maximum entropy method, Voronoi cells |
| Divisions: | Faculty of Science and Engineering > School of Engineering |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 09 Jan 2023 09:43 |
| Last Modified: | 16 Dec 2023 02:30 |
| DOI: | 10.1016/j.ress.2022.109031 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3166844 |
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