A fast-convergence algorithm for reliability analysis based on the AK-MCS

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dc.contributor.authorXiong, Yifang
dc.contributor.authorSampath, Suresh
dc.date.accessioned2021-04-20T13:48:55Z
dc.date.available2021-04-20T13:48:55Z
dc.date.issued2021-04-16
dc.description.abstractIn the field of reliability engineering, assessing the probability of failure of an event is usually a computationally demanding task. One way of tackling this issue is by metamodelling, in which the original computational-expensive model is approximated by a simpler metamodel. A method called AK-MCS for Active learning reliability method combining Kriging and Monte Carlo Simulation, was developed for the metamodel construction, and proved effective in reliability analysis. However, the performance of the AK-MCS algorithm is sensitive to the candidate size and the Kriging trend. Moreover, it cannot take advantage of parallel computing, a highly efficient way to speed up the simulation process. Focusing on the identified issues, this study proposes three methods to improve algorithm performance: the candidate size control method, multiple trends method, and weighted clustering method. These three methods are integrated into the AK-MCS structure, with their individual and combined performances being tested using four examples. Results suggest that all three methods contribute to the improvement of algorithm efficiency. When the three methods working together, the computational time is reduced significantly, and in the meantime, higher accuracy can be achieved.en_UK
dc.identifier.citationXiong Y, Sampath S. (2021) A fast-convergence algorithm for reliability analysis based on the AK-MCS. Reliability Engineering and System Safety, Volume 213, September 2021, Article number 107693en_UK
dc.identifier.issn0951-8320
dc.identifier.urihttps://doi.org/10.1016/j.ress.2021.107693
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16600
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectReliabilityen_UK
dc.subjectKrigingen_UK
dc.subjectAdaptive refinementen_UK
dc.subjectMonte Carlo simulationen_UK
dc.titleA fast-convergence algorithm for reliability analysis based on the AK-MCSen_UK
dc.typeArticleen_UK

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