Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76456
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dc.contributor.authorWang, Fen_US
dc.contributor.authorLi, Hen_US
dc.date.accessioned2018-05-10T02:56:00Z-
dc.date.available2018-05-10T02:56:00Z-
dc.date.issued2017-
dc.identifier.citationStructural safety, 2017, v. 69, p. 1-10en_US
dc.identifier.issn0167-4730-
dc.identifier.urihttp://hdl.handle.net/10397/76456-
dc.description.abstractReliability evaluation under incomplete probability information (prescribed marginal distributions and correlation coefficients) is a challenging task. The widely used Nataf transformation inherently assumes a normal copula for dependence modeling, which can be inappropriate in some cases. This paper aims to provide a more general isoprobabilistic transformation method for reliability evaluations under incomplete probability information. To this end, the joint probability distribution is represented using the pair-copula decomposition approach, which is highly flexible in dependence modeling. The desired pair-copula parameters are retrieved from the incomplete probability information by a simulation based method. Finally, based on the reconstructed joint probability distribution, the Rosenblatt's transformation is adopted for the subsequent reliability evaluation. The proposed method is illustrated in a tunnel excavation reliability problem. Several dependence structures characterized by different pair copulas are investigated to provide insights into the effect of copula selection on reliability results.en_US
dc.description.sponsorshipDepartment of Building and Real Estateen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofStructural safetyen_US
dc.subjectIncomplete probability informationen_US
dc.subjectCorrelated multivariatesen_US
dc.subjectPair-copulasen_US
dc.subjectRosenblatt's transformationen_US
dc.subjectReliabilityen_US
dc.titleTowards reliability evaluation involving correlated multivariates under incomplete probability information : a reconstructed joint probability distribution for isoprobabilistic transformationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage10-
dc.identifier.volume69-
dc.identifier.doi10.1016/j.strusafe.2017.07.002-
dc.identifier.isiWOS:000413057300001-
dc.identifier.eissn1879-3355-
dc.identifier.rosgroupid2017002680-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201805 bcrc-
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