Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/29085
Full metadata record
DC FieldValueLanguage
dc.contributor.authorVan Vledder, Gerbrant Ph.-
dc.date.accessioned2022-10-13T11:30:22Z-
dc.date.available2022-10-13T11:30:22Z-
dc.date.issued2016-12-19-
dc.identifier.citationAkpınar, A. vd. (2017). ''Long-term analysis of wave power potential in the Black Sea, based on 31-year SWAN simulations''. Ocean Engineering, 130, 482-497.en_US
dc.identifier.issn0029-8018-
dc.identifier.urihttps://doi.org/10.1016/j.oceaneng.2016.12.023-
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0029801816306096-
dc.identifier.urihttp://hdl.handle.net/11452/29085-
dc.description.abstractThis study analyzes the wave energy potential in the Black Sea based on long-term model simulations. A dataset covering the period of 1979-2009 is produced using a calibrated numerical wave prediction model (SWAN). This dataset was analyzed in detail to determine the wave energy potential to enable a reliable and optimal design of wave energy conversion devices in the Black Sea. This analysis provides information on the long-term variability as well as on the annual, seasonal and monthly averages. The analysis of the hindcast results is conducted on a spatial and a location scale. The spatial analysis provides information for the entire Black Sea on; the averaged mean wave energy flux over the period 1979-2009, and the decades 1980-1989, 1990-1999, and 2000-2009, seasonal and monthly averages of wave energy flux during 31 years, variability indices for the 1979-2009 period, and variabilities on monthly and seasonality basis based on inter-annual averages during 31 years. The location scale considered nine locations providing information on; wave power roses, probabilities of occurrence and cumulative distribution functions of wave power in different power ranges, variation and trend of yearly average wave power, seasonal average wave power and its annual variations, and quantities of wave energy flux for different H-m0 and Tm-10 ranges. Results show that areas with the highest wave energy potential are located in the south-western part of the Black Sea. These areas are; Burgas - Rezovo (BR) with an average annual total energy of 43.9 MW h/m followed by Dolni Chiflik - Shkorpilovtsi (DCS) with 37.3 MW h/m and Istanbul - Alacali (IA) with 36.1 MW h/m.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEngineeringen_US
dc.subjectOceanographyen_US
dc.subjectBlack Seaen_US
dc.subjectResource variabilityen_US
dc.subjectSpatial distributionen_US
dc.subjectSWAN modelen_US
dc.subjectWave power assessmenten_US
dc.subjectEnergy resource assessmenten_US
dc.subjectCoastal regionsen_US
dc.subjectModelen_US
dc.subjectWinden_US
dc.subjectSensitivityen_US
dc.subjectHindcasten_US
dc.subjectAtlasen_US
dc.subjectBlack Seaen_US
dc.subjectRosaen_US
dc.subjectDistribution functionsen_US
dc.subjectEnergy conversionen_US
dc.subjectLocationen_US
dc.subjectProbability distributionsen_US
dc.subjectSpatial distributionen_US
dc.subjectWave poweren_US
dc.subjectBlack seaen_US
dc.subjectCumulative distribution functionen_US
dc.subjectLong term analysisen_US
dc.subjectLong-term variabilityen_US
dc.subjectResource variabilityen_US
dc.subjectSWAN modelen_US
dc.subjectWave energy potentialen_US
dc.subjectWave prediction modelsen_US
dc.subjectEnergy resourceen_US
dc.subjectNumerical modelen_US
dc.subjectSpatial distributionen_US
dc.subjectWave energyen_US
dc.subjectWave poweren_US
dc.subjectWave energy conversionen_US
dc.titleLong-term analysis of wave power potential in the Black Sea, based on 31-year SWAN simulationsen_US
dc.typeArticleen_US
dc.identifier.wos000393000700040tr_TR
dc.identifier.scopus2-s2.0-85007137543tr_TR
dc.relation.tubitak214M436tr_TR
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi/İnşaat Mühendisliği Bölümü.tr_TR
dc.contributor.orcid0000-0002-9042-6851tr_TR
dc.contributor.orcid0000-0003-4496-5974tr_TR
dc.identifier.startpage482tr_TR
dc.identifier.endpage497tr_TR
dc.identifier.volume130tr_TR
dc.relation.journalOcean Engineeringen_US
dc.contributor.buuauthorAkpınar, Adem-
dc.contributor.buuauthorBingölbali, Bilal-
dc.contributor.researcheridABE-8817-2020tr_TR
dc.contributor.researcheridAAC-6763-2019tr_TR
dc.contributor.researcheridAAB-4152-2020tr_TR
dc.relation.collaborationYurt dışıtr_TR
dc.relation.collaborationSanayitr_TR
dc.subject.wosEngineering, marineen_US
dc.subject.wosEngineering, civilen_US
dc.subject.wosEngineering, oceanen_US
dc.subject.wosOceanographyen_US
dc.indexed.wosSCIEen_US
dc.indexed.scopusScopusen_US
dc.wos.quartileQ2en_US
dc.wos.quartileQ1en_US
dc.contributor.scopusid23026855400tr_TR
dc.contributor.scopusid57189584264tr_TR
dc.subject.scopusWave Energy; Wind Power; Data Buoyen_US
Appears in Collections:Scopus
Web of Science

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.