Sensitivity of sample for simulation-based reliability analysis methods

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dc.identifier.uri http://dx.doi.org/10.15488/10642
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/10720
dc.contributor.author Yuan, Xiukai
dc.contributor.author Gu, Jian
dc.contributor.author Liu, Shaolong
dc.date.accessioned 2021-03-26T08:44:49Z
dc.date.available 2021-03-26T08:44:49Z
dc.date.issued 2021
dc.identifier.citation Yuan, X.; Gu, J.; Liu, S.: Sensitivity of sample for simulation-based reliability analysis methods. In: CMES - Computer Modeling in Engineering and Sciences 126 (2021), Nr. 1, S. 331-357. DOI: https://doi.org/10.32604/CMES.2021.010482
dc.description.abstract In structural reliability analysis, simulation methods are widely used. The statistical characteristics of failure probability estimate of these methods have been well investigated. In this study, the sensitivities of the failure probability estimate and its statistical characteristics with regard to sample, called 'contribution indexes', are proposed to measure the contribution of sample. The contribution indexes in four widely simulation methods, i.e., Monte Carlo simulation (MCS), importance sampling (IS), line sampling (LS) and subset simulation (SS) are derived and analyzed. The proposed contribution indexes of sample can provide valuable information understanding the methods deeply, and enlighten potential improvement of methods. It is found that the main differences between these investigated methods lie in the contribution indexes of the safety samples, which are the main factors to the efficiency of the methods. Moreover, numerical examples are used to validate these findings. © This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. eng
dc.language.iso eng
dc.publisher Palmdale, Calif. : Tech Science Press
dc.relation.ispartofseries CMES - Computer Modeling in Engineering and Sciences 126 (2021), Nr. 1
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject importance sampling eng
dc.subject line sampling eng
dc.subject Monte Carlo simulation eng
dc.subject reliability analysis eng
dc.subject subset simulation eng
dc.subject.ddc 004 | Informatik ger
dc.subject.ddc 600 | Technik ger
dc.title Sensitivity of sample for simulation-based reliability analysis methods
dc.type Article
dc.type Text
dc.relation.essn 1526-1506
dc.relation.issn 1526-1492
dc.relation.doi https://doi.org/10.32604/CMES.2021.010482
dc.bibliographicCitation.issue 1
dc.bibliographicCitation.volume 126
dc.bibliographicCitation.firstPage 331
dc.bibliographicCitation.lastPage 357
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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