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Global failure probability function estimation based on an adaptive strategy and combination algorithm.
- Source :
-
Reliability Engineering & System Safety . Mar2023, Vol. 231, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- The failure probability function (FPF) expresses the probability of failure as a function of the distribution parameters associated with the random variables of a reliability problem. Knowledge on this FPF is of much relevance for reliability sensitivity analysis and reliability-based design optimisation. However, its calculation is usually a challenging task. Therefore, this paper presents an efficient approach for estimating the FPF based on an adaptive strategy and a combination algorithm. The proposed approach involves three basic elements: (1) a Weighted Importance Sampling approach, which allows determining local FPF estimates; (2) an adaptive strategy for determining at which realisations of the distribution parameters it is necessary to perform local FPF estimation; and (3) an optimal combination algorithm, which allows to aggregate local FPF estimations together to form a global estimate of the FPF. Test and practical examples are presented to demonstrate the efficiency and feasibility of the proposed approach. • A global approach for failure probability function estimation is proposed. • It utilises weighted importance sampling to efficiently obtain local estimators. • It includes an adaptive active strategy to guide the local estimations. • It adopts an optimal combination algorithm to combine the local FPF estimators. [ABSTRACT FROM AUTHOR]
- Subjects :
- *PROBABILITY theory
*ALGORITHMS
*SENSITIVITY analysis
*PARAMETER estimation
Subjects
Details
- Language :
- English
- ISSN :
- 09518320
- Volume :
- 231
- Database :
- Academic Search Index
- Journal :
- Reliability Engineering & System Safety
- Publication Type :
- Academic Journal
- Accession number :
- 160910487
- Full Text :
- https://doi.org/10.1016/j.ress.2022.108937