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dc.contributor.authorKatsikogiannis, George
dc.contributor.authorHaver, Sverre Kristian
dc.contributor.authorBachynski-Polic, Erin Elizabeth
dc.date.accessioned2024-01-11T12:42:12Z
dc.date.available2024-01-11T12:42:12Z
dc.date.created2024-01-09T09:52:59Z
dc.date.issued2024
dc.identifier.issn0141-1187
dc.identifier.urihttps://hdl.handle.net/11250/3111116
dc.description.abstractThis study examines the influence of probabilistic models for wave parameters in the joint environmental model and hydrodynamic/soil models on extreme mudline bending moments for monopile-based wind turbines at representative wind speeds, using the environmental contour method. For significant wave height, the 3-parameter Weibull model using the method of moments (MoM) provides the best fit to hindcast data across different wind classes, for the statistical models and data considered in the study. The hybrid Log-normal-Weibull (LonoWe) model also provides a reasonable fit but is sensitive to the transition point between distributions. Both models yield the largest extreme responses, with differences of approximately 0.5–3.5%. The 3-parameter Weibull model with maximum likelihood estimation (MLE) and the 2-parameter Weibull model result in less conservative contours, leading to up to 13% lower extreme responses, compared to LonoWe and Weibull (MoM). Regarding peak period, both the Log-normal and 3-parameter Weibull models provide reasonable fits, with the latter being more accurate near the steepness (breaking) limit. The stochastic variation among maxima due to seed variability and the uncertainty in quantile estimates as a function of number of samples was found to be crucial, particularly for severe sea states at the cut-out speed. Soil modelling is particularly important when the turbine is parked and encounters peak wave periods close to the turbine’s natural periods, while the effect of soil modelling on the extremes during turbine operation is negligible. Additionally, the impact of diffraction becomes relatively important for short wave periods. However, it is worth noting that the choice of load models has less impact on extreme responses compared to variations in the contours caused by different statistical models or seed variability.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAssessing some statistical and physical modelling uncertainties of extreme responses for monopile-based offshore wind turbines, using metocean contoursen_US
dc.title.alternativeAssessing some statistical and physical modelling uncertainties of extreme responses for monopile-based offshore wind turbines, using metocean contoursen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.journalApplied Ocean Researchen_US
dc.identifier.doi10.1016/j.apor.2024.103880
dc.identifier.cristin2222855
dc.relation.projectNorges forskningsråd: 268182en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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