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dc.contributor.authorStieng, Lars Einar
dc.contributor.authorHetland, Ruth
dc.contributor.authorSchafhirt, Sebastian
dc.contributor.authorMuskulus, Michael
dc.date.accessioned2016-09-22T10:45:47Z
dc.date.accessioned2016-09-29T14:23:51Z
dc.date.available2016-09-22T10:45:47Z
dc.date.available2016-09-29T14:23:51Z
dc.date.issued2015
dc.identifier.citationEnergy Procedia 2015, 80:229-236nb_NO
dc.identifier.issn1876-6102
dc.identifier.urihttp://hdl.handle.net/11250/2412062
dc.description.abstractTime domain analyses of Offshore Wind Turbines involve a lot of computational effort. In this paper, we present a method for reducing this effort by using results from analyses with shorter simulation lengths to predict the results of the longer simulations lengths required by the standards. This involves using simple statistical treatment of the first 10 minutes of simulation data, and a subsequent linear regression, to predict the damage equivalent load of the full 60 minutes simulation. With some reservations about the general applicability of the method, the results are promising. Some suggestions for further investigations and developments of the presented methods are discussed.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.rightsNavngivelse-Ikkekommersiell-IngenBearbeidelse 3.0 Norge*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/no/*
dc.titleRelative assessment of fatigue loads for offshore wind turbine support structuresnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.date.updated2016-09-22T10:45:47Z
dc.source.volume80nb_NO
dc.source.journalEnergy Procedianb_NO
dc.identifier.doi10.1016/j.egypro.2015.11.426
dc.identifier.cristin1297439
dc.relation.projectNorges forskningsråd: 193823nb_NO
dc.description.localcode© 2015 The Authors. Published by Elsevier. This is an open access article under the CC BY-NC-ND license.nb_NO


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Navngivelse-Ikkekommersiell-IngenBearbeidelse 3.0 Norge
Except where otherwise noted, this item's license is described as Navngivelse-Ikkekommersiell-IngenBearbeidelse 3.0 Norge