Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/9111
Title: Small failure probability: principles, progress and perspectives
Authors: Lee, Ikjin
Lee, Ungki
Ramu, Palaniappan
Yadav, Deepanshu
Bayrak, Gamze
Acar, Erdem
Keywords: Extreme value statistics
High reliability
Machine learning
Rare event
Sampling
Small failure probability
Surrogate model
Rare-Event Probability
Importance Sampling Method
Support Vector Regression
Adaptive Directional Stratification
Structural Reliability Assessment
Extreme-Value Distribution
Artificial Neural-Network
Subset Simulation Method
Monte-Carlo
Cross-Entropy
Issue Date: 2022
Publisher: Springer
Abstract: Design of structural and multidisciplinary systems under uncertainties requires estimation of their reliability or equivalently the probability of failure under the given operating conditions. Various high technology systems including aircraft and nuclear power plants are designed for very small probabilities of failure, and estimation of these small probabilities is computationally challenging. Even though substantial number of approaches have been proposed to reduce the computational burden, there is no established guideline to decide which approach is the best choice for a given problem. This paper provides a review of the approaches developed for small probability estimation of structural or multidisciplinary systems and enlists the criterion/metrics to choose the preferred approach amongst the existing ones, for a given problem. First, the existing approaches are categorized into the sampling-based, the surrogate-based, and statistics of extremes based approaches. Next, the small probability estimation methods developed for time-independent systems and the ones tailored for time-dependent systems are discussed, respectively. Then, some real-life engineering applications in structural and multidisciplinary design studies are summarized. Finally, concluding remarks are provided, and areas for future research are suggested.
URI: https://doi.org/10.1007/s00158-022-03431-6
https://hdl.handle.net/20.500.11851/9111
ISSN: 1615-147X
1615-1488
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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