Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6794
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dc.contributor.authorAcar, Erdem-
dc.date.accessioned2021-09-11T15:43:36Z-
dc.date.available2021-09-11T15:43:36Z-
dc.date.issued2011en_US
dc.identifier.issn0954-4062-
dc.identifier.urihttps://doi.org/10.1177/2041298310392833-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6794-
dc.description.abstractClassical tail modelling is based on performing a relatively small number of limit-state calculations through Monte Carlo sampling, and then fitting a generalized Pareto distribution to the tail part of the data. The limit-state calculations that do not belong to the tail part are discarded. To reduce the amount of discarded data, this article proposes an efficient tail modelling procedure based on guiding the limit-state evaluations towards the sampling points that have high chances of yielding limit-state values falling into the tail region. The guidance of the limit-state evaluations is achieved through a procedure that utilizes limit-state approximation and distribution fitting. The accuracy of the proposed method is tested through a mathematical problem and four structural mechanics problems, and it is found that the accuracy of reliability estimations can be significantly increased compared to classical tail modelling techniques for the same number of limit-state function evaluations. In addition, it is also found that the improvement in accuracy can be traded off for reducing the number of limit-state evaluations.en_US
dc.description.sponsorshipTUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [MAG-109M537]en_US
dc.description.sponsorshipThe funding provided by the TUBITAK under Grant No. MAG-109M537 is gratefully acknowledged.en_US
dc.language.isoenen_US
dc.publisherProfessional Engineering Publishing Ltden_US
dc.relation.ispartofProceedings of The Institution of Mechanical Engineers Part C-Journal of Mechanical Engineering Scienceen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjecttail modellingen_US
dc.subjecthigh reliabilityen_US
dc.subjectguided Monte Carlo simulationsen_US
dc.titleGuided tail modelling for efficient and accurate reliability estimation of highly safe mechanical systemsen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Mechanical Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Makine Mühendisliği Bölümütr_TR
dc.identifier.volume225en_US
dc.identifier.issueC5en_US
dc.identifier.startpage1237en_US
dc.identifier.endpage1251en_US
dc.authorid0000-0002-3661-5563-
dc.authorid0000-0002-3661-5563-
dc.identifier.wosWOS:000291267100019en_US
dc.identifier.scopus2-s2.0-79956042765en_US
dc.institutionauthorAcar, Erdem-
dc.identifier.doi10.1177/2041298310392833-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.7. Department of Mechanical Engineering-
Appears in Collections:Makine Mühendisliği Bölümü / Department of Mechanical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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