On the use of constrained focused waves for characteristic load prediction
dc.contributor.author | Tosdevin, Tom | |
dc.contributor.author | Jin, Siya | |
dc.contributor.author | Simmonds, Dave | |
dc.contributor.author | Hann, Martyn | |
dc.contributor.author | Greaves, Deborah | |
dc.contributor.other | Faculty of Science & Engineering | en_US |
dc.date.accessioned | 2022-10-18T12:43:12Z | |
dc.date.available | 2022-10-18T12:43:12Z | |
dc.date.issued | 2022-11 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/19706 | |
dc.description.abstract |
Physical experiments investigating the extreme responses of a semi-submersible floating offshore wind turbine were conducted to allow a comparison of design wave methods. A 1:70 scale model of the IEA 15MW reference turbine and VolturnUS-S platform was studied focusing on the hydrodynamics under parked turbine conditions. A comparison of characteristic load predictions was made between design standard recommendations by the IEC and DNV covering different design wave types and post processing methods. Constrained waves are permitted for predicting characteristic loads for fixed offshore turbines but the extent to which they are suitable for floating devices is questionable. A constrained wave method for characteristic load prediction is applied and it is concluded that in general characteristic responses related to pitch may be estimated well with single response conditioned focused waves but for response types where the low frequency surge is important, e.g. mooring loads, constrained focused waves need to be applied. | en_US |
dc.language.iso | en | |
dc.publisher | University of Plymouth | en |
dc.subject | Floating wind, semi-sub, extreme response, reliability, focused wave, short design wave | en_US |
dc.title | On the use of constrained focused waves for characteristic load prediction | en_US |
dc.type | Article | en_US |
plymouth.date-start | 2018-2019 | en_US |
rioxxterms.funder | Engineering and Physical Sciences Research Council | en_US |
rioxxterms.identifier.project | Supergen ORE hub 2018 | en_US |