Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine
Hydrokinetic turbines are devices that harness the power from moving water of rivers, canals, and artificial currents without the construction of a dam. The design optimization of the rotor is the most important stage to maximize the power production. The rotor is designed to convert the kinetic ene...
- Autores:
-
Aguilar Bedoya, Jonathan
Rubio Clemente, Ainhoa
Velásquez García, Laura Isabel
Chica Arrieta, Edwin Lenin
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2019
- Institución:
- Tecnológico de Antioquia
- Repositorio:
- Repositorio Tdea
- Idioma:
- eng
- OAI Identifier:
- oai:dspace.tdea.edu.co:tdea/2808
- Acceso en línea:
- https://dspace.tdea.edu.co/handle/tdea/2808
- Palabra clave:
- Renewable energy
Energia renovável
Energía renovable
Hydropower
Renewable energy technologies
Hydroelectric power
Energía hidroeléctrica
Optimization
Optimización
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by/4.0/
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Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine |
| title |
Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine |
| spellingShingle |
Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine Renewable energy Energia renovável Energía renovable Hydropower Renewable energy technologies Hydroelectric power Energía hidroeléctrica Optimization Optimización |
| title_short |
Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine |
| title_full |
Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine |
| title_fullStr |
Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine |
| title_full_unstemmed |
Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine |
| title_sort |
Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic Turbine |
| dc.creator.fl_str_mv |
Aguilar Bedoya, Jonathan Rubio Clemente, Ainhoa Velásquez García, Laura Isabel Chica Arrieta, Edwin Lenin |
| dc.contributor.author.none.fl_str_mv |
Aguilar Bedoya, Jonathan Rubio Clemente, Ainhoa Velásquez García, Laura Isabel Chica Arrieta, Edwin Lenin |
| dc.subject.agrovoc.none.fl_str_mv |
Renewable energy Energia renovável Energía renovable |
| topic |
Renewable energy Energia renovável Energía renovable Hydropower Renewable energy technologies Hydroelectric power Energía hidroeléctrica Optimization Optimización |
| dc.subject.proposal.none.fl_str_mv |
Hydropower Renewable energy technologies |
| dc.subject.unesco.none.fl_str_mv |
Hydroelectric power Energía hidroeléctrica Optimization Optimización |
| description |
Hydrokinetic turbines are devices that harness the power from moving water of rivers, canals, and artificial currents without the construction of a dam. The design optimization of the rotor is the most important stage to maximize the power production. The rotor is designed to convert the kinetic energy of the water current into mechanical rotation energy, which is subsequently converted into electrical energy by an electric generator. The rotor blades are critical components that have a large impact on the performance of the turbine. These elements are designed from traditional hydrodynamic profiles (hydrofoils), to directly interact with the water current. Operational e ectiveness of the hydrokinetic turbines depends on their performance, which is measured by using the ratio between the lift coe cient (CL) and the drag coe cient (CD) of the selected hydrofoil. High lift forces at low flow rates are required in the design of the blades; therefore, the use of multi-element hydrofoils is commonly regarded as an adequate solution to achieve this goal. In this study, 2D CFD simulations and multi-objective optimization methodology based on surrogate modelling were conducted to design an appropriate multi-element hydrofoil to be used in a horizontal-axis hydrokinetic turbine. The Eppler 420 hydrofoil was utilized for the design of the multi-element hydrofoil composed of a main element and a flap. The multi-element design selected as the optimal one had a gap of 2.825% of the chord length (C1), an overlap of 8.52 %C1, a flap deflection angle ( ) of 19.765 , a flap chord length (C2) of 42.471 %C1, and an angle of attack ( ) of –4 . Keywords: hydropower; optimization; renewable energy technologies |
| publishDate |
2019 |
| dc.date.issued.none.fl_str_mv |
2019 |
| dc.date.accessioned.none.fl_str_mv |
2023-04-20T03:20:47Z |
| dc.date.available.none.fl_str_mv |
2023-04-20T03:20:47Z |
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Artículo de revista |
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Text |
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info:eu-repo/semantics/article |
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http://purl.org/redcol/resource_type/ART |
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1996-1073 |
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eng |
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eng |
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1 |
| dc.relation.citationvolume.spa.fl_str_mv |
12 |
| dc.relation.ispartofjournal.spa.fl_str_mv |
Energies |
| dc.relation.references.spa.fl_str_mv |
Dusek, J.E. Leading Edge Vortex Detection Using Bio-Inspired On-Body Pressure Sensing. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 2011. Sóbester, A.; Forrester, A.I.J. Aircraft Aerodynamic Design: Geometry and Optimization; John Wiley & Sons: Hoboken, NJ, USA, 2014; ISBN 9781118534748 Aiguabella Macau, R. Formula One Rear Wing Optimization. Available online: https://upcommons.upc.edu/ handle/2099.1/12270 (accessed on 5 June 2019). Ragheb, A.M.; Selig, M.S. Multielement Airfoils for Wind Turbines. In Wind Energy Engineering; Elsevier: Amsterdam, The Netherlands, 2017; pp. 203–219, ISBN 9780128094518. Sood, I. Multi-Element Blade Design forMW-ScaleWind Turbines. In Proceedings of the 17th AIAA Aviation Technology, Integration, and Operations Conference, Denver, CO, USA, 5–9 June 2017. Timmer,W.A.; Rooij, R.P.J.O.M. Summary of the Delft UniversityWind Turbine Dedicated Airfoils. J. Sol. Energy Eng. 2003, 125, 488–496. [CrossRef] Van Rooij, R.P.J.O.M.; Timmer, W.A. Roughness Sensitivity Considerations for Thick Rotor Blade Airfoils. J. Sol. Energy Eng. 2003, 125, 468–478. [CrossRef] Chica, E.; Rubio-Clemente, A. Design of Zero Head Turbines for Power Generation. In Renewable Hydropower Technologies; InTech: London, UK, 2017. [CrossRef] Nunes, M.M.; Mendes, R.C.F.; Oliveira, T.F.; Brasil Junior, A.C.P. An experimental study on the di user-enhanced propeller hydrokinetic turbines. Renew. Energy 2019, 133, 840–848. [CrossRef] Niebuhr, C.M.; van Dijk, M.; Neary, V.S.; Bhagwan, J.N. A review of hydrokinetic turbines and enhancement techniques for canal installations: Technology, applicability and potential. Renew. Sustain. Energy Rev. 2019, 113, 109240. [CrossRef] Wang, W.Q.; Yin, R.; Yan, Y. Design and prediction hydrodynamic performance of horizontal axis micro-hydrokinetic river turbine. Renew. Energy 2019, 133, 91–102. [CrossRef] Kumar, D.; Sarkar, S. A review on the technology, performance, design optimization, reliability, techno-economics and environmental impacts of hydrokinetic energy conversion systems. Renew. Sustain. Energy Rev. 2016, 58, 796–813. [CrossRef] Jenne, D.S.; Yu, Y.H.; Neary, V. Levelized Cost of Energy Analysis of Marine and Hydrokinetic Reference Models (No. NREL/CP-5000-64013); National Renewable Energy Lab. (NREL): Golden, CO, USA, 2015. Neary, V.S.; Lawson, M.; Previsic, M.; Copping, A.; Hallett, K.C.; LaBonte, A.; Murray, D. Methodology for Design and Economic Analysis of Marine Energy Conversion (MEC) Technologies (No. SAND2014-3561C); Sandia National Lab. (SNL-NM): Albuquerque, NM, USA, 2014. Kang, S.; Yang, X.; Sotiropoulos, F. On the onset of wake meandering for an axial flow turbine in a turbulent open channel flow. J. Fluid Mech. 2014, 744, 376–403. [CrossRef] Kang, S.; Borazjani, I.; Colby, J.A.; Sotiropoulos, F. Numerical simulation of 3D flow past a real-life marine hydrokinetic turbine. Adv. Water Resour. 2012, 39, 33–43. [CrossRef] Haas, K.A.; Muscalus, A.C. Marine Hydrokinetic Energy: Tidal Streams. In Advances in Coastal Hydraulics; World Scientific Publishing Company: Singapore, 2018; pp. 457–491. Hill, C.; Musa, M.; Guala, M. Interaction between instream axial flow hydrokinetic turbines and uni-directional flow bedforms. Renew. Energy 2016, 86, 409–421. [CrossRef] Gotelli, C.; Musa, M.; Guala, M.; Escauriaza, C. Experimental and Numerical Investigation of Wake Interactions of Marine Hydrokinetic Turbines. Energies 2019, 12, 3188. [CrossRef] Musa, M.; Hill, C.; Sotiropoulos, F.; Guala, M. Performance and resilience of hydrokinetic turbine arrays under large migrating fluvial bedforms. Nat. Energy 2019, 3, 839. [CrossRef] Yavuz, T.; Koç, E. Performance analysis of double blade airfoil for hydrokinetic turbine applications. Energy Convers. Manag. 2012, 63, 95–100. [CrossRef] Narsipur, S.; Pomeroy, B.; Selig, M. CFD Analysis of Multielement Airfoils forWind Turbines. In Proceedings of the 30th AIAA Applied Aerodynamics Conference, New Orleans, LA, USA, 25–28 June 2012. Zahle, F.; Gaunaa, M.; Sørensen, N.N.; Bak, C. Design and wind tunnel testing of a thick, multi-element high-lift airfoil. In Proceedings of the European Wind Energy Conference and Exhibition 2012, EWEC 2012, Copenhagen, Denmark, 16–19 April 2012. Ragheb, A.; Selig, M. Multi-Element Airfoil Configurations forWind Turbines. In Proceedings of the 29th AIAA Applied Aerodynamics Conference, Honolulu, HI, USA, 27–30 June 2011. Caughey, D.A.; Hafez, M.M. Frontiers of Computational Fluid Dynamics 2006;World Scientific Publishing Co Pte Ltd.: Singapore, 2005; ISBN 9789812703187. Yondo, R.; Andrés, E.; Valero, E. A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses. Prog. Aerosp. Sci. 2018, 96, 23–61. [CrossRef] Han, Z.; Zhang, K.; Song, W.; Liu, J. Surrogate-based Aerodynamic Shape Optimization with Application to Wind Turbine Airfoils. In Proceedings of the 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Grapevine, TX, USA, 7–10 January 2013. Forrester, A.I.J. Engineering Design via Surrogate Modelling: A Practical Guide—Constructing a Surrogate; Wiley: Hoboken, NJ, USA, 2008; ISBN 9780470770801. Demange, J.; Savill, A.M.; Kipouros, T. A Multifidelity Multiobjective Optimization Framework for High-Lift Airfoils. In Proceedings of the 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Washington, DC, USA, 13–17 June 2016. Jo, Y.; Yi, S.; Choi, S.; Lee, D.-J.; Choi, D.-Z. Adaptive Variable-Fidelity Analysis and Design Using Dynamic Fidelity Indicators. AIAA J. 2016, 54, 3564–3579. [CrossRef] Demange, J.; Savill, A.M.; Kipouros, T. Multifidelity Optimization for High-Lift Airfoils. In Proceedings of the 54th AIAA Aerospace Sciences Meeting, San Diego, CA, USA, 4–8 January 2016. Kontogiannis, S.G.; Demange, J.; Kipouros, T.; Savill, A.M. A comparison study of two multifidelity methods for aerodynamic optimization. In Proceedings of the 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Kissimmee, FL, USA, 8–12 January 2018. Kanazaki, M.; Tanaka, K.; Jeong, S.; Yamamoto, K. Multi-Objective Aerodynamic Exploration of Elements’ Setting for High-Lift Airfoil Using Kriging Model. J. Aircr. 2007, 44, 858–864. [CrossRef] Jeong, S.; Murayama, M.; Yamamoto, K. E cient Optimization Design Method Using Kriging Model. J. Aircr. 2005, 42, 1375. [CrossRef] Li, D. Multi-Objective Design Optimization for High-Lift Aircraft Configurations Supported by Surrogate Modeling. Master’s Thesis, Cranfield University, Cranfield, UK, 2013. Benini, E.; Ponza, R.; Massaro, A. High-Lift Multi-Element Airfoil Shape and Setting Optimization Using Multi-Objective Evolutionary Algorithms. J. Aircr. 2011, 48, 683–696. [CrossRef] MATLAB R2019a; MathWorks Inc: Natick, MA, USA, 2019. Deb, K. Multi-Objective Optimization Using Evolutionary Algorithms; John Wiley & Sons: Hoboken, NJ, USA, 2008; ISBN 9780470743614 Yavuz, T.; Koç, E.; Kilki¸s, B.; Erol, T.; Balas, C.; Aydemir, T. Performance analysis of the airfoil-slat arrangements for hydro and wind turbine applications. Renew. Energy 2015, 74, 414–421. [CrossRef] Chica, E.; Perez, F.; Rubio-Clemente, A.; Agudelo, S. Design of a hydrokinetic turbine. WIT Trans. Ecol. Environ. 2015, 195, 137–148. Xu, L.; Baglietto, E.; Brizzolara, S. Extending the applicability of RANS turbulence closures to the simulation of transitional flow around hydrofoils at low Reynolds number. Ocean Eng. 2018, 164, 1–12. [CrossRef] Dajani, S.; Shehadeh, M.; Saqr, K.M.; Elbatran, A.H.; Hart, N.; Soliman, A.; Cheshire, D. Numerical Study for a Marine Current Turbine Blade Performance under Varying Angle of Attack. Energy Procedia 2017, 119, 898–909. [CrossRef] Soulat, L.; Fosso Pouangué, A.; Moreau, S. A high-order sensitivity method for multi-element high-lift device optimization. Comput. Fluids 2016, 124, 105–116. [CrossRef] Carlton, J.S. Marine Propellers and Propulsion; Elsevier: Amsterdam, The Netherlands, 2012; ISBN 9780080971247. Molland, A.F.; Bahaj, A.S.; Chaplin, J.R.; Batten,W.M.J. Measurements and predictions of forces, pressures and cavitation on 2-D sections suitable for marine current turbines. Proc. Inst. Mech. Eng. Part M J. Eng. Marit. Environ. 2004, 218, 127–138. [CrossRef] Chica, E.; Aguilar, J.; Rubio Clemente, A. Analysis of a lift augmented hydrofoil for hydrokinetic turbines. Renew. Energy Power Qual. J. 2019, 17, 49–55. [CrossRef] Coiro, D.P.; Maisto, U.; Scherillo, F.; Melone, S.; Grasso, F. Horizontal Axis Tidal Current Turbine: Numerical and Experimental Investigations. In Proceedings of the Owemes, Civitavecchia, Italy, 20–22 April 2006. ANSYS FLUENT. ANSYS Fluent 19 R1 User’s Guide; Ansys Inc: Canonsburg, PA, UAS, 2009. Menter, F.R. Two-equation eddy-viscosity turbulence models for engineering applications. AIAA J. 1994, 32, 1598. [CrossRef] Schleicher, W.C.; Riglin, J.D.; Oztekin, A. Numerical characterization of a preliminary portable micro-hydrokinetic turbine rotor design. Renew. Energy 2015, 76, 237–241. [CrossRef] Silva, P.A.S.F.; De Oliveira, T.F.; Brasil Junior, A.C.P.; Vaz, J.R.P. Numerical study of wake characteristics in a horizontal-axis hydrokinetic turbine. An. Acad. Bras. Cienc. 2016, 88, 1678–2690. [CrossRef] Gorle, J.M.R.; Chatellier, L.; Pons, F.; Ba, M. Flow and performance analysis of H-Darrieus hydroturbine in a confined flow: A computational and experimental study. J. Fluids Struct. 2016, 66, 382–402. [CrossRef] Wang, X.; Song, B.; Wang, P.; Sun, C. Hydrofoil optimization of underwater glider using Free-Form Deformation and surrogate-based optimization. Int. J. Nav. Archit. Ocean Eng. 2018, 10, 730–740. [CrossRef] Ribeiro, A.F.P.; Awruch, A.M.; Gomes, H.M. An airfoil optimization technique for wind turbines. Appl. Math. Model. 2012, 36, 4898–4907. [CrossRef] Ding, X.; Peng, M.; Shen, M.; Zhu, L.; Che, H.; Zhou, S.; Li, G.; Liu, R. Wind Power Forecasting Based on Extended Latin Hypercube Sampling; Atlantis Press: Paris, France, 2016. Bernardini, E.; Spence, S.M.J.;Wei, D.; Kareem, A. Aerodynamic shape optimization of civil structures: A CFD-enabled Kriging-based approach. J. Wind Eng. Ind. Aerodyn. 2015, 144, 154–164. [CrossRef] Arias-Montano, A.; Coello Coello, C.A.; Mezura-Montes, E. Multi-objective airfoil shape optimization using a multiple-surrogate approach. In Proceedings of the 2012 IEEE Congress on Evolutionary Computation, Brisbane, Australia, 10–15 June 2012; pp. 1–8. Trapani, G. The Design of High Lift Aircraft Configurations through Multi-Objective Optimisation. Ph.D. Thesis, Cranfield University, Cranfield, UK, 2014. IHS ESDU.ESDU94026: Introduction to the Estimation of the Lift Coe cients at Zero Angle of Attack and at Maximum Lift for Aerofoils with High-Lift Devices at Low Speeds; IHS ESDU: London, UK, 2000; ISBN 978-0-85679-913-6. Coello, C.A.; Lamont, G.B.; Van Veldhuisen, D.A. Evolutionary Algorithms for Solving Multi-Objective Problems; Springer: Berlin, Germany, 2007; ISBN 9780387332543 Zitzler, E.; Thiele, L. Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 1999, 3, 257–271. [CrossRef] Auger, A.; Bader, J.; Brockho , D.; Zitzler, E. Theory of the hypervolume indicator: Optimal -distributions and the choice of the reference point. In Proceedings of the 10th ACM SIGEVOWorkshop on Foundations of Genetic Algorithms, FOGA’09, Orlando, FL, USA, 9–11 January 2009. Zitzler, E.; Thiele, L.; Laumanns, M.; Fonseca, C.M.; da Fonseca,V.G. Performance assessment of multiobjective optimizers: An analysis and review. IEEE Trans. Evol. Comput. 2003, 7, 117–132. [CrossRef] Wilcoxon, F. Individual Comparisons by Ranking Methods. Biom. Bull. 1945, 1, 80. [CrossRef] |
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Aguilar Bedoya, Jonathan80cce53b-b8d9-402e-9ca3-16e60e2d7354Rubio Clemente, Ainhoa8924cc9a-a600-460b-b180-3288281741e5Velásquez García, Laura Isabel11a92509-a1af-4051-a2d5-dccfe020846eChica Arrieta, Edwin Lenina3a70685-f160-43b7-8bd2-46fcfa5c040e2023-04-20T03:20:47Z2023-04-20T03:20:47Z2019https://dspace.tdea.edu.co/handle/tdea/28081996-1073Hydrokinetic turbines are devices that harness the power from moving water of rivers, canals, and artificial currents without the construction of a dam. The design optimization of the rotor is the most important stage to maximize the power production. The rotor is designed to convert the kinetic energy of the water current into mechanical rotation energy, which is subsequently converted into electrical energy by an electric generator. The rotor blades are critical components that have a large impact on the performance of the turbine. These elements are designed from traditional hydrodynamic profiles (hydrofoils), to directly interact with the water current. Operational e ectiveness of the hydrokinetic turbines depends on their performance, which is measured by using the ratio between the lift coe cient (CL) and the drag coe cient (CD) of the selected hydrofoil. High lift forces at low flow rates are required in the design of the blades; therefore, the use of multi-element hydrofoils is commonly regarded as an adequate solution to achieve this goal. In this study, 2D CFD simulations and multi-objective optimization methodology based on surrogate modelling were conducted to design an appropriate multi-element hydrofoil to be used in a horizontal-axis hydrokinetic turbine. The Eppler 420 hydrofoil was utilized for the design of the multi-element hydrofoil composed of a main element and a flap. The multi-element design selected as the optimal one had a gap of 2.825% of the chord length (C1), an overlap of 8.52 %C1, a flap deflection angle ( ) of 19.765 , a flap chord length (C2) of 42.471 %C1, and an angle of attack ( ) of –4 . Keywords: hydropower; optimization; renewable energy technologies18 páginasapplication/pdfengMDPISuizahttps://creativecommons.org/licenses/by/4.0/Atribución 4.0 Internacional (CC BY 4.0)info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://www.mdpi.com/1996-1073/12/24/4679Design and Optimization of a Multi-Element Hydrofoil for a Horizontal-Axis Hydrokinetic TurbineArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a851824112EnergiesDusek, J.E. Leading Edge Vortex Detection Using Bio-Inspired On-Body Pressure Sensing. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 2011.Sóbester, A.; Forrester, A.I.J. Aircraft Aerodynamic Design: Geometry and Optimization; John Wiley & Sons: Hoboken, NJ, USA, 2014; ISBN 9781118534748Aiguabella Macau, R. Formula One Rear Wing Optimization. Available online: https://upcommons.upc.edu/ handle/2099.1/12270 (accessed on 5 June 2019).Ragheb, A.M.; Selig, M.S. Multielement Airfoils for Wind Turbines. In Wind Energy Engineering; Elsevier: Amsterdam, The Netherlands, 2017; pp. 203–219, ISBN 9780128094518.Sood, I. Multi-Element Blade Design forMW-ScaleWind Turbines. In Proceedings of the 17th AIAA Aviation Technology, Integration, and Operations Conference, Denver, CO, USA, 5–9 June 2017.Timmer,W.A.; Rooij, R.P.J.O.M. Summary of the Delft UniversityWind Turbine Dedicated Airfoils. J. Sol. Energy Eng. 2003, 125, 488–496. [CrossRef]Van Rooij, R.P.J.O.M.; Timmer, W.A. Roughness Sensitivity Considerations for Thick Rotor Blade Airfoils. J. Sol. Energy Eng. 2003, 125, 468–478. [CrossRef]Chica, E.; Rubio-Clemente, A. Design of Zero Head Turbines for Power Generation. In Renewable Hydropower Technologies; InTech: London, UK, 2017. [CrossRef]Nunes, M.M.; Mendes, R.C.F.; Oliveira, T.F.; Brasil Junior, A.C.P. An experimental study on the di user-enhanced propeller hydrokinetic turbines. Renew. Energy 2019, 133, 840–848. [CrossRef]Niebuhr, C.M.; van Dijk, M.; Neary, V.S.; Bhagwan, J.N. A review of hydrokinetic turbines and enhancement techniques for canal installations: Technology, applicability and potential. Renew. Sustain. Energy Rev. 2019, 113, 109240. [CrossRef]Wang, W.Q.; Yin, R.; Yan, Y. Design and prediction hydrodynamic performance of horizontal axis micro-hydrokinetic river turbine. Renew. Energy 2019, 133, 91–102. [CrossRef]Kumar, D.; Sarkar, S. A review on the technology, performance, design optimization, reliability, techno-economics and environmental impacts of hydrokinetic energy conversion systems. Renew. Sustain. Energy Rev. 2016, 58, 796–813. [CrossRef]Jenne, D.S.; Yu, Y.H.; Neary, V. Levelized Cost of Energy Analysis of Marine and Hydrokinetic Reference Models (No. NREL/CP-5000-64013); National Renewable Energy Lab. (NREL): Golden, CO, USA, 2015.Neary, V.S.; Lawson, M.; Previsic, M.; Copping, A.; Hallett, K.C.; LaBonte, A.; Murray, D. Methodology for Design and Economic Analysis of Marine Energy Conversion (MEC) Technologies (No. SAND2014-3561C); Sandia National Lab. (SNL-NM): Albuquerque, NM, USA, 2014.Kang, S.; Yang, X.; Sotiropoulos, F. On the onset of wake meandering for an axial flow turbine in a turbulent open channel flow. J. Fluid Mech. 2014, 744, 376–403. [CrossRef]Kang, S.; Borazjani, I.; Colby, J.A.; Sotiropoulos, F. Numerical simulation of 3D flow past a real-life marine hydrokinetic turbine. Adv. Water Resour. 2012, 39, 33–43. [CrossRef]Haas, K.A.; Muscalus, A.C. Marine Hydrokinetic Energy: Tidal Streams. In Advances in Coastal Hydraulics; World Scientific Publishing Company: Singapore, 2018; pp. 457–491.Hill, C.; Musa, M.; Guala, M. Interaction between instream axial flow hydrokinetic turbines and uni-directional flow bedforms. Renew. Energy 2016, 86, 409–421. [CrossRef]Gotelli, C.; Musa, M.; Guala, M.; Escauriaza, C. Experimental and Numerical Investigation of Wake Interactions of Marine Hydrokinetic Turbines. Energies 2019, 12, 3188. [CrossRef]Musa, M.; Hill, C.; Sotiropoulos, F.; Guala, M. Performance and resilience of hydrokinetic turbine arrays under large migrating fluvial bedforms. Nat. Energy 2019, 3, 839. [CrossRef]Yavuz, T.; Koç, E. Performance analysis of double blade airfoil for hydrokinetic turbine applications. Energy Convers. Manag. 2012, 63, 95–100. [CrossRef]Narsipur, S.; Pomeroy, B.; Selig, M. CFD Analysis of Multielement Airfoils forWind Turbines. In Proceedings of the 30th AIAA Applied Aerodynamics Conference, New Orleans, LA, USA, 25–28 June 2012.Zahle, F.; Gaunaa, M.; Sørensen, N.N.; Bak, C. Design and wind tunnel testing of a thick, multi-element high-lift airfoil. In Proceedings of the European Wind Energy Conference and Exhibition 2012, EWEC 2012, Copenhagen, Denmark, 16–19 April 2012.Ragheb, A.; Selig, M. Multi-Element Airfoil Configurations forWind Turbines. In Proceedings of the 29th AIAA Applied Aerodynamics Conference, Honolulu, HI, USA, 27–30 June 2011.Caughey, D.A.; Hafez, M.M. Frontiers of Computational Fluid Dynamics 2006;World Scientific Publishing Co Pte Ltd.: Singapore, 2005; ISBN 9789812703187.Yondo, R.; Andrés, E.; Valero, E. A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses. Prog. Aerosp. Sci. 2018, 96, 23–61. [CrossRef]Han, Z.; Zhang, K.; Song, W.; Liu, J. Surrogate-based Aerodynamic Shape Optimization with Application to Wind Turbine Airfoils. In Proceedings of the 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Grapevine, TX, USA, 7–10 January 2013.Forrester, A.I.J. Engineering Design via Surrogate Modelling: A Practical Guide—Constructing a Surrogate; Wiley: Hoboken, NJ, USA, 2008; ISBN 9780470770801.Demange, J.; Savill, A.M.; Kipouros, T. A Multifidelity Multiobjective Optimization Framework for High-Lift Airfoils. In Proceedings of the 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Washington, DC, USA, 13–17 June 2016.Jo, Y.; Yi, S.; Choi, S.; Lee, D.-J.; Choi, D.-Z. Adaptive Variable-Fidelity Analysis and Design Using Dynamic Fidelity Indicators. AIAA J. 2016, 54, 3564–3579. [CrossRef]Demange, J.; Savill, A.M.; Kipouros, T. Multifidelity Optimization for High-Lift Airfoils. In Proceedings of the 54th AIAA Aerospace Sciences Meeting, San Diego, CA, USA, 4–8 January 2016.Kontogiannis, S.G.; Demange, J.; Kipouros, T.; Savill, A.M. A comparison study of two multifidelity methods for aerodynamic optimization. In Proceedings of the 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Kissimmee, FL, USA, 8–12 January 2018.Kanazaki, M.; Tanaka, K.; Jeong, S.; Yamamoto, K. Multi-Objective Aerodynamic Exploration of Elements’ Setting for High-Lift Airfoil Using Kriging Model. J. Aircr. 2007, 44, 858–864. [CrossRef]Jeong, S.; Murayama, M.; Yamamoto, K. E cient Optimization Design Method Using Kriging Model. J. Aircr. 2005, 42, 1375. [CrossRef]Li, D. Multi-Objective Design Optimization for High-Lift Aircraft Configurations Supported by Surrogate Modeling. Master’s Thesis, Cranfield University, Cranfield, UK, 2013.Benini, E.; Ponza, R.; Massaro, A. High-Lift Multi-Element Airfoil Shape and Setting Optimization Using Multi-Objective Evolutionary Algorithms. J. Aircr. 2011, 48, 683–696. [CrossRef]MATLAB R2019a; MathWorks Inc: Natick, MA, USA, 2019.Deb, K. Multi-Objective Optimization Using Evolutionary Algorithms; John Wiley & Sons: Hoboken, NJ, USA, 2008; ISBN 9780470743614Yavuz, T.; Koç, E.; Kilki¸s, B.; Erol, T.; Balas, C.; Aydemir, T. Performance analysis of the airfoil-slat arrangements for hydro and wind turbine applications. Renew. Energy 2015, 74, 414–421. [CrossRef]Chica, E.; Perez, F.; Rubio-Clemente, A.; Agudelo, S. Design of a hydrokinetic turbine. WIT Trans. Ecol. Environ. 2015, 195, 137–148.Xu, L.; Baglietto, E.; Brizzolara, S. Extending the applicability of RANS turbulence closures to the simulation of transitional flow around hydrofoils at low Reynolds number. Ocean Eng. 2018, 164, 1–12. [CrossRef]Dajani, S.; Shehadeh, M.; Saqr, K.M.; Elbatran, A.H.; Hart, N.; Soliman, A.; Cheshire, D. Numerical Study for a Marine Current Turbine Blade Performance under Varying Angle of Attack. Energy Procedia 2017, 119, 898–909. [CrossRef]Soulat, L.; Fosso Pouangué, A.; Moreau, S. A high-order sensitivity method for multi-element high-lift device optimization. Comput. Fluids 2016, 124, 105–116. [CrossRef]Carlton, J.S. Marine Propellers and Propulsion; Elsevier: Amsterdam, The Netherlands, 2012; ISBN 9780080971247.Molland, A.F.; Bahaj, A.S.; Chaplin, J.R.; Batten,W.M.J. Measurements and predictions of forces, pressures and cavitation on 2-D sections suitable for marine current turbines. Proc. Inst. Mech. Eng. Part M J. Eng. Marit. Environ. 2004, 218, 127–138. [CrossRef]Chica, E.; Aguilar, J.; Rubio Clemente, A. Analysis of a lift augmented hydrofoil for hydrokinetic turbines. Renew. Energy Power Qual. J. 2019, 17, 49–55. [CrossRef]Coiro, D.P.; Maisto, U.; Scherillo, F.; Melone, S.; Grasso, F. Horizontal Axis Tidal Current Turbine: Numerical and Experimental Investigations. In Proceedings of the Owemes, Civitavecchia, Italy, 20–22 April 2006.ANSYS FLUENT. ANSYS Fluent 19 R1 User’s Guide; Ansys Inc: Canonsburg, PA, UAS, 2009.Menter, F.R. Two-equation eddy-viscosity turbulence models for engineering applications. AIAA J. 1994, 32, 1598. [CrossRef]Schleicher, W.C.; Riglin, J.D.; Oztekin, A. Numerical characterization of a preliminary portable micro-hydrokinetic turbine rotor design. Renew. Energy 2015, 76, 237–241. [CrossRef]Silva, P.A.S.F.; De Oliveira, T.F.; Brasil Junior, A.C.P.; Vaz, J.R.P. Numerical study of wake characteristics in a horizontal-axis hydrokinetic turbine. An. Acad. Bras. Cienc. 2016, 88, 1678–2690. [CrossRef]Gorle, J.M.R.; Chatellier, L.; Pons, F.; Ba, M. Flow and performance analysis of H-Darrieus hydroturbine in a confined flow: A computational and experimental study. J. Fluids Struct. 2016, 66, 382–402. [CrossRef]Wang, X.; Song, B.; Wang, P.; Sun, C. Hydrofoil optimization of underwater glider using Free-Form Deformation and surrogate-based optimization. Int. J. Nav. Archit. Ocean Eng. 2018, 10, 730–740. [CrossRef]Ribeiro, A.F.P.; Awruch, A.M.; Gomes, H.M. An airfoil optimization technique for wind turbines. Appl. Math. Model. 2012, 36, 4898–4907. [CrossRef]Ding, X.; Peng, M.; Shen, M.; Zhu, L.; Che, H.; Zhou, S.; Li, G.; Liu, R. Wind Power Forecasting Based on Extended Latin Hypercube Sampling; Atlantis Press: Paris, France, 2016.Bernardini, E.; Spence, S.M.J.;Wei, D.; Kareem, A. Aerodynamic shape optimization of civil structures: A CFD-enabled Kriging-based approach. J. Wind Eng. Ind. Aerodyn. 2015, 144, 154–164. [CrossRef]Arias-Montano, A.; Coello Coello, C.A.; Mezura-Montes, E. Multi-objective airfoil shape optimization using a multiple-surrogate approach. In Proceedings of the 2012 IEEE Congress on Evolutionary Computation, Brisbane, Australia, 10–15 June 2012; pp. 1–8.Trapani, G. The Design of High Lift Aircraft Configurations through Multi-Objective Optimisation. Ph.D. Thesis, Cranfield University, Cranfield, UK, 2014.IHS ESDU.ESDU94026: Introduction to the Estimation of the Lift Coe cients at Zero Angle of Attack and at Maximum Lift for Aerofoils with High-Lift Devices at Low Speeds; IHS ESDU: London, UK, 2000; ISBN 978-0-85679-913-6.Coello, C.A.; Lamont, G.B.; Van Veldhuisen, D.A. Evolutionary Algorithms for Solving Multi-Objective Problems; Springer: Berlin, Germany, 2007; ISBN 9780387332543Zitzler, E.; Thiele, L. Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 1999, 3, 257–271. [CrossRef]Auger, A.; Bader, J.; Brockho , D.; Zitzler, E. Theory of the hypervolume indicator: Optimal -distributions and the choice of the reference point. In Proceedings of the 10th ACM SIGEVOWorkshop on Foundations of Genetic Algorithms, FOGA’09, Orlando, FL, USA, 9–11 January 2009.Zitzler, E.; Thiele, L.; Laumanns, M.; Fonseca, C.M.; da Fonseca,V.G. Performance assessment of multiobjective optimizers: An analysis and review. IEEE Trans. Evol. Comput. 2003, 7, 117–132. [CrossRef]Wilcoxon, F. Individual Comparisons by Ranking Methods. Biom. Bull. 1945, 1, 80. 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 incorporada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.
 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