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dc.contributor.authorSclavounos, Paul D
dc.contributor.authorZhang, Yu
dc.contributor.authorMa, Yu
dc.contributor.authorLarson, David F. H
dc.date.accessioned2020-12-10T21:55:38Z
dc.date.available2020-12-10T21:55:38Z
dc.date.issued2017-09
dc.date.submitted2017-06
dc.identifier.isbn9780791857779
dc.identifier.urihttps://hdl.handle.net/1721.1/128784
dc.description.abstractThe development is presented of an analytical model for the prediction of the stochastic nonlinear wave loads on the support structure of bottom mounted and floating offshore wind turbines. Explicit expressions are derived for the time-domain nonlinear exciting forces in a seastate with significant wave height comparable to the diameter of the support structure based on the fluid impulse theory. The method is validated against experimental measurements with good agreement. The higher order moments of the nonlinear load are evaluated from simulated force records and the derivation of analytical expressions for the nonlinear load statistics for their efficient use in design is addressed. The identification of the inertia and drag coefficients of a generalized nonlinear wave load model trained against experiments using Support Vector Machine learning algorithms is discussed.en_US
dc.publisherAmerican Society of Mechanical Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1115/OMAE2017-61184en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceASMEen_US
dc.titleOffshore Wind Turbine Nonlinear Wave Loads and Their Statisticsen_US
dc.typeArticleen_US
dc.identifier.citationSclavounos, Paul D., Yu Zhang, Yu Ma, and David F. Larson. “Offshore Wind Turbine Nonlinear Wave Loads and Their Statistics.” International Conference on Ocean, Offshore and Arctic Engineering, Volume 9: Offshore Geotechnics; Torgeir Moan Honoring Symposium (September 2017): OMAE2017-61184, V009T12A042 © 2017 ASMEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
dc.relation.journalInternational Conference on Ocean, Offshore and Arctic Engineeringen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2018-12-20T16:35:07Z
dspace.orderedauthorsSclavounos, Paul D.; Zhang, Yu; Ma, Yu; Larson, David F.en_US
dspace.embargo.termsNen_US
dspace.date.submission2019-04-04T14:18:03Z
mit.journal.volumeVolume 9: Offshore Geotechnics; Torgeir Moan Honoring Symposiumen_US
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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