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dc.date.accessioned2020-02-03T20:07:08Z
dc.date.available2020-02-03T20:07:08Z
dc.date.created2018-06-19T11:01:04Z
dc.date.issued2018
dc.identifier.citationFazeres-Ferradosa, Tiago Taveira-Pinto, Francisco Vanem, Erik Reis, Maria Teresa das Neves, Luciana . Asymmetric copula–based distribution models for met-ocean data in offshore wind engineering applications. Wind Engineering : The International Journal of Wind Power. 2018, 42(4), 304-334
dc.identifier.urihttp://hdl.handle.net/10852/72661
dc.description.abstractJoint statistical models for long-term wave climate are a key aspect of offshore wind engineering design. However, to find a joint model for sea-state characteristics is often difficult due to the complex nature of the wave climate and the physical constraints of sea-states phenomena. The available records of wave heights and periods are often very asymmetric in their nature. This article presents a copula-based approach to obtain the joint cumulative distribution function of the significant wave heights and the up-crossing mean period. This study is based on 124-month hindcast data concerning Horns Rev 3 offshore wind farm. The extra-parametrization technique of symmetric copulas is implemented to account for the asymmetry present in the data. The analysis of the total sea, the wind-sea and primary swell components is performed separately. The results show that the extra-parametrization technique with pairwise copulas consistently provided a better goodness-of-fit when compared to symmetric copulas. Moreover, it is demonstrated that the separation of the total sea into its components does not always improve the extra-parametrized copula’s performance. Furthermore, this article also discusses copulas application to offshore wind engineering.
dc.languageEN
dc.titleAsymmetric copula–based distribution models for met-ocean data in offshore wind engineering applications
dc.typeJournal article
dc.creator.authorFazeres-Ferradosa, Tiago
dc.creator.authorTaveira-Pinto, Francisco
dc.creator.authorVanem, Erik
dc.creator.authorReis, Maria Teresa
dc.creator.authordas Neves, Luciana
cristin.unitcode185,15,13,0
cristin.unitnameMatematisk institutt
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.cristin1592212
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Wind Engineering : The International Journal of Wind Power&rft.volume=42&rft.spage=304&rft.date=2018
dc.identifier.jtitleWind Engineering : The International Journal of Wind Power
dc.identifier.volume42
dc.identifier.issue4
dc.identifier.startpage304
dc.identifier.endpage334
dc.identifier.doihttps://doi.org/10.1177/0309524X18777323
dc.identifier.urnURN:NBN:no-75787
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn0309-524X
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/72661/1/v2%2BFazeres-Ferradosa%2BTiago%2Bmanuscript.pdf
dc.type.versionAcceptedVersion
dc.relation.projectNFR/249261


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