Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA

Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-qu...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Deb, Mithun [verfasserIn] Yang, Zhaoqing [verfasserIn] Wang, Taiping [verfasserIn] Kilcher, Levi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization

Übergeordnetes Werk:	Enthalten in: Renewable energy - Amsterdam [u.a.] : Elsevier Science, 1991, 219
Übergeordnetes Werk:	volume:219

DOI / URN:	10.1016/j.renene.2023.04.100

Katalog-ID:	ELV065825136

Internformat


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520			\|a Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment.
650		4	\|a Marine renewable energy
650		4	\|a Tidal stream energy
650		4	\|a Turbulence
650		4	\|a Numerical modeling
650		4	\|a Tidal energy converters
650		4	\|a Resource characterization
700	1		\|a Yang, Zhaoqing \|e verfasserin \|4 aut
700	1		\|a Wang, Taiping \|e verfasserin \|4 aut
700	1		\|a Kilcher, Levi \|e verfasserin \|4 aut
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allfields	10.1016/j.renene.2023.04.100 doi (DE-627)ELV065825136 (ELSEVIER)S0960-1481(23)00564-5 DE-627 ger DE-627 rda eng 530 620 VZ 52.56 bkl Deb, Mithun verfasserin (orcid)0000-0001-8898-3096 aut Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment. Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization Yang, Zhaoqing verfasserin aut Wang, Taiping verfasserin aut Kilcher, Levi verfasserin aut Enthalten in Renewable energy Amsterdam [u.a.] : Elsevier Science, 1991 219 Online-Ressource (DE-627)320412091 (DE-600)2001449-1 (DE-576)252613937 1879-0682 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.56 Regenerative Energieformen alternative Energieformen VZ AR 219
spelling	10.1016/j.renene.2023.04.100 doi (DE-627)ELV065825136 (ELSEVIER)S0960-1481(23)00564-5 DE-627 ger DE-627 rda eng 530 620 VZ 52.56 bkl Deb, Mithun verfasserin (orcid)0000-0001-8898-3096 aut Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment. Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization Yang, Zhaoqing verfasserin aut Wang, Taiping verfasserin aut Kilcher, Levi verfasserin aut Enthalten in Renewable energy Amsterdam [u.a.] : Elsevier Science, 1991 219 Online-Ressource (DE-627)320412091 (DE-600)2001449-1 (DE-576)252613937 1879-0682 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.56 Regenerative Energieformen alternative Energieformen VZ AR 219
allfields_unstemmed	10.1016/j.renene.2023.04.100 doi (DE-627)ELV065825136 (ELSEVIER)S0960-1481(23)00564-5 DE-627 ger DE-627 rda eng 530 620 VZ 52.56 bkl Deb, Mithun verfasserin (orcid)0000-0001-8898-3096 aut Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment. Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization Yang, Zhaoqing verfasserin aut Wang, Taiping verfasserin aut Kilcher, Levi verfasserin aut Enthalten in Renewable energy Amsterdam [u.a.] : Elsevier Science, 1991 219 Online-Ressource (DE-627)320412091 (DE-600)2001449-1 (DE-576)252613937 1879-0682 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.56 Regenerative Energieformen alternative Energieformen VZ AR 219
allfieldsGer	10.1016/j.renene.2023.04.100 doi (DE-627)ELV065825136 (ELSEVIER)S0960-1481(23)00564-5 DE-627 ger DE-627 rda eng 530 620 VZ 52.56 bkl Deb, Mithun verfasserin (orcid)0000-0001-8898-3096 aut Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment. Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization Yang, Zhaoqing verfasserin aut Wang, Taiping verfasserin aut Kilcher, Levi verfasserin aut Enthalten in Renewable energy Amsterdam [u.a.] : Elsevier Science, 1991 219 Online-Ressource (DE-627)320412091 (DE-600)2001449-1 (DE-576)252613937 1879-0682 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.56 Regenerative Energieformen alternative Energieformen VZ AR 219
allfieldsSound	10.1016/j.renene.2023.04.100 doi (DE-627)ELV065825136 (ELSEVIER)S0960-1481(23)00564-5 DE-627 ger DE-627 rda eng 530 620 VZ 52.56 bkl Deb, Mithun verfasserin (orcid)0000-0001-8898-3096 aut Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment. Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization Yang, Zhaoqing verfasserin aut Wang, Taiping verfasserin aut Kilcher, Levi verfasserin aut Enthalten in Renewable energy Amsterdam [u.a.] : Elsevier Science, 1991 219 Online-Ressource (DE-627)320412091 (DE-600)2001449-1 (DE-576)252613937 1879-0682 nnns volume:219 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.56 Regenerative Energieformen alternative Energieformen VZ AR 219
language	English
source	Enthalten in Renewable energy 219 volume:219
sourceStr	Enthalten in Renewable energy 219 volume:219
format_phy_str_mv	Article
bklname	Regenerative Energieformen alternative Energieformen
institution	findex.gbv.de
topic_facet	Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization
dewey-raw	530
isfreeaccess_bool	false
container_title	Renewable energy
authorswithroles_txt_mv	Deb, Mithun @@aut@@ Yang, Zhaoqing @@aut@@ Wang, Taiping @@aut@@ Kilcher, Levi @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320412091
dewey-sort	3530
id	ELV065825136
language_de	englisch
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author	Deb, Mithun
spellingShingle	Deb, Mithun ddc 530 bkl 52.56 misc Marine renewable energy misc Tidal stream energy misc Turbulence misc Numerical modeling misc Tidal energy converters misc Resource characterization Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA
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topic_title	530 620 VZ 52.56 bkl Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA Marine renewable energy Tidal stream energy Turbulence Numerical modeling Tidal energy converters Resource characterization
topic	ddc 530 bkl 52.56 misc Marine renewable energy misc Tidal stream energy misc Turbulence misc Numerical modeling misc Tidal energy converters misc Resource characterization
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title	Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA
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title_full	Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA
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title_sort	turbulence modeling to aid tidal energy resource characterization in the western passage, maine, usa
title_auth	Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA
abstract	Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment.
abstractGer	Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment.
abstract_unstemmed	Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment.
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title_short	Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA
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up_date	2024-07-07T00:22:49.975Z
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Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA

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