Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade

The hydrodynamic shape of a blade is one of the most important factors in the design process of a horizontal axis hydrokinetic turbine that influences its performance. The present work is focused on the design and hydrodynamic analysis of a high-lift system using the optimization method of surrogate...

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Autores:
Rubio Clemente, Ainhoa
Aguilar Bedoya, Jonathan
Chica Arrieta, Edwin Lenin
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Tecnológico de Antioquia
Repositorio:
Repositorio Tdea
Idioma:
eng
OAI Identifier:
oai:dspace.tdea.edu.co:tdea/2805
Acceso en línea:
https://dspace.tdea.edu.co/handle/tdea/2805
Palabra clave:
Computational fluid dynamics
Horizontal axis hydrokinetic turbine
Surrogate model
High-lift system
Multielement hydrofoil
Rights
openAccess
License
http://purl.org/coar/access_right/c_abf2
id RepoTdea2_7573a5c334e08cbb03c56c7b51a8cdca
oai_identifier_str oai:dspace.tdea.edu.co:tdea/2805
network_acronym_str RepoTdea2
network_name_str Repositorio Tdea
repository_id_str
dc.title.none.fl_str_mv Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
title Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
spellingShingle Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
Computational fluid dynamics
Horizontal axis hydrokinetic turbine
Surrogate model
High-lift system
Multielement hydrofoil
title_short Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
title_full Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
title_fullStr Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
title_full_unstemmed Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
title_sort Surrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade
dc.creator.fl_str_mv Rubio Clemente, Ainhoa
Aguilar Bedoya, Jonathan
Chica Arrieta, Edwin Lenin
dc.contributor.author.none.fl_str_mv Rubio Clemente, Ainhoa
Aguilar Bedoya, Jonathan
Chica Arrieta, Edwin Lenin
dc.subject.other.none.fl_str_mv Computational fluid dynamics
topic Computational fluid dynamics
Horizontal axis hydrokinetic turbine
Surrogate model
High-lift system
Multielement hydrofoil
dc.subject.proposal.none.fl_str_mv Horizontal axis hydrokinetic turbine
Surrogate model
High-lift system
Multielement hydrofoil
description The hydrodynamic shape of a blade is one of the most important factors in the design process of a horizontal axis hydrokinetic turbine that influences its performance. The present work is focused on the design and hydrodynamic analysis of a high-lift system using the optimization method of surrogate models and computational fluid dynamics (CFD) analysis. The parameters that affect the amount of the lift and the drag force that a hydrofoil can generate are the gap, the overlap, the flap deflection angle (δ), the flap chord length (C2) and the angle of attack of the hydrofoil (α). These factors were varied to examine the turbine performance in terms of the ratio between the lift (CL) and the drag coefficient (CD), and the minimum negative pressure coefficient (min Cpre) in order to avoid the cavitation inception. For this propose, surrogate models were implemented to analyse the CFD results and find the optimal combination of the design parameters of the high-lift hydrofoil. The traditional Eppler 420 hydrofoil was utilized for the design of the multi-element profile, which was composed of a main element and a flap. The multi-element design selected as optimal had a gap of 2.825 %C1, an overlap of 8.52 %C1, a δ of 19.765˚, a C2 of 42.471 %C1 and a α of -4˚, where C1 refers to the chord length of the main element. In comparison with the traditional Eppler 420 hydrofoil, CL/CD ratio increases from 39.050 to 42.517. Key words. Horizontal axis hydrokinetic turbine, surrogate model, computational fluid dynamics, high-lift system, multielement hydrofoil
publishDate 2020
dc.date.issued.none.fl_str_mv 2020
dc.date.accessioned.none.fl_str_mv 2023-04-19T21:47:44Z
dc.date.available.none.fl_str_mv 2023-04-19T21:47:44Z
dc.type.spa.fl_str_mv Artículo de revista
Documento de Conferencia
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dc.relation.ispartofjournal.spa.fl_str_mv Renewable energy & power quality journal
dc.relation.references.spa.fl_str_mv D. Kumar and S. Sarkar, “A review on the technology, performance, design optimization, reliability, techno-economics and environmental impacts of hydrokinetic energy conversion systems”, Renewable and Sustainable Energy Reviews, (2016). Vol. 58, pp. 796-813.
E. Chica and A. Rubio-Clemente, “Design of Zero Head Turbines for Power Generation”, Renewable Hydropower Technologies Basel I. Ismail, IntechOpen, DOI: 10.5772/66907. Available from: https://www.intechopen.com/books/renewablehydropower-technologies/design-of-zero-head-turbines-forpower-generation. July 26th 2017
E. Chica, J. Aguilar and A. Rubio-Clemente, “Analysis of a lift augmented hydrofoil for hydrokinetic turbines”, Renewable Energy and Power Quality Journal, (2019). Vol. 17, pp. 49-55
J. Aguilar, A. Rubio-Clemente, L. Velàsquez and E. Chica. “Design and optimization of a multi-element hydrofoil for a horizontal-axis hydrokinetic turbine”, Energies, (2019), Vol. 12 (4679), pp. 1-18
E. Chica, J. Aguilar and A. Rubio-Clemente, “Investigación numérica sobre el uso de álabes multi-elemento en turbina hidrocinética de eje horizontal”, Revista UIS Ingenierías, (2019). Vol. 10 (3), pp. 117-128.
E. Benini, R. Ponza and A. Massaro, “High-lift multielement airfoil shape and setting optimization using multiobjective evolutionary algorithms”, Journal of Aircraft, (2011). Vol. 48(2), pp. 683-696
P.M. Kumar, J. Seo, W. Seok, S.H. Rhee and A. Samad, “Multi-fidelity optimization of blade thickness parameters for a horizontal axis tidal stream turbine”, Renewable energy, (2019). Vol. 135, pp. 277-287
A.I. Forrester, N.W. Bressloff and A.J. Keane, “Optimization using surrogate models and partially converged computational fluid dynamics simulations”, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, (2006). Vol 462(2071), pp. 2177-2204.
R. Yondo, E. Andres and E. Valero, “A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses”, Progress in Aerospace Sciences, (2018). Vol. 96, pp. 23-61.
S. Jeong, M. Murayama and K. Yamamoto, “Efficient optimization design method using kriging model”, Journal of aircraft, (2005). Vol. 42(2), pp. 413-420.
J.D. Feldhacker, B.A. Jones, A. Doostan and J. Hampton, “Reduced cost mission design using surrogate models”, Advances in Space Research, (2016). Vol. 57(2), pp. 588-603
V. Díaz-Casás, J.A Becerra, F. Lopez-Peña and R.J. Duro, “Wind turbine design through evolutionary algorithms based on surrogate CFD methods”, Optimization and engineering, (2013). Vol. 14(2), pp. 305-329
A.D.V. Carrasco, D.J. Valles-Rosales, L.C. Mendez and M.I. Rodriguez, “A site-specific design of a fixed-pitch fixedspeed wind turbine blade for energy optimization using surrogate models”, Renewable energy, (2016). Vol. 88, pp. 112- 119.
A.F. Molland, A.S Bahaj, J.R. Chaplin and W.M.J. Batten, “Measurements and predictions of forces, pressures and cavitation on 2-D sections suitable for marine current turbines”, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, (2004). Vol. 218(2), pp. 127-138
P.A.S.F da Silva, L.D. Shinomiya, T.F. de Oliveira, J.R.P. Vaz, A.L.A. Mesquita and A.C.P.B. Junior, “Design of hydrokinetic turbine blades considering cavitation”, Energy Procedia, (2015). Vol. 75, pp. 277-282.
N.V. Qoeipo, R.T. Haftka, W. Shyy, T. Goel, R. Vaidyanathan, and P.K. Tucker, “Surrogate-based analysis and optimization”, Progress in Aerospace Sci-ences, (2005). Vol. 41 (1), pp. 1–28
A. Bhosekar and M. Ierapetritou, “Advances in surrogate based modeling, feasibility analysis, and optimization: A review”, Computers & Chemical Engineering, (2018). Vol. 108, pp. 250-267.
L. Leifsson, E. Hermannsson and S. Koziel, “Optimal shape design of multi-element trawl-doors using local surrogate models”, Journal of Computational Science, (2015). Vol. 10, pp. 55-62.
Y. Jin, “A comprehensive survey of fitness approximation in evolutionary computation”, Soft computing, (2005). Vol. 9(1), pp. 3-12.
A.F.P. Ribeiro, A.M. Awruch and H.M. Gomes, “An airfoil optimization technique for wind turbines”, Applied Mathematical Modelling, (2012). Vol. 36(10), pp. 4898-4907.
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spelling Rubio Clemente, Ainhoa8924cc9a-a600-460b-b180-3288281741e5Aguilar Bedoya, Jonathan80cce53b-b8d9-402e-9ca3-16e60e2d7354Chica Arrieta, Edwin Lenina3a70685-f160-43b7-8bd2-46fcfa5c040e2023-04-19T21:47:44Z2023-04-19T21:47:44Z2020https://dspace.tdea.edu.co/handle/tdea/28052172-038XThe hydrodynamic shape of a blade is one of the most important factors in the design process of a horizontal axis hydrokinetic turbine that influences its performance. The present work is focused on the design and hydrodynamic analysis of a high-lift system using the optimization method of surrogate models and computational fluid dynamics (CFD) analysis. The parameters that affect the amount of the lift and the drag force that a hydrofoil can generate are the gap, the overlap, the flap deflection angle (δ), the flap chord length (C2) and the angle of attack of the hydrofoil (α). These factors were varied to examine the turbine performance in terms of the ratio between the lift (CL) and the drag coefficient (CD), and the minimum negative pressure coefficient (min Cpre) in order to avoid the cavitation inception. For this propose, surrogate models were implemented to analyse the CFD results and find the optimal combination of the design parameters of the high-lift hydrofoil. The traditional Eppler 420 hydrofoil was utilized for the design of the multi-element profile, which was composed of a main element and a flap. The multi-element design selected as optimal had a gap of 2.825 %C1, an overlap of 8.52 %C1, a δ of 19.765˚, a C2 of 42.471 %C1 and a α of -4˚, where C1 refers to the chord length of the main element. In comparison with the traditional Eppler 420 hydrofoil, CL/CD ratio increases from 39.050 to 42.517. Key words. Horizontal axis hydrokinetic turbine, surrogate model, computational fluid dynamics, high-lift system, multielement hydrofoil6 páginasapplication/pdfengElsevier BVEspañahttps://www.icrepq.com/icrepq20/258-20-rubio.pdfComputational fluid dynamicsHorizontal axis hydrokinetic turbineSurrogate modelHigh-lift systemMultielement hydrofoilSurrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine bladeArtículo de revistaDocumento de Conferenciahttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/resource_type/c_c94fTextinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/conferenceObjecthttp://purl.org/redcol/resource_type/EChttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a8516015518Renewable energy & power quality journalD. Kumar and S. Sarkar, “A review on the technology, performance, design optimization, reliability, techno-economics and environmental impacts of hydrokinetic energy conversion systems”, Renewable and Sustainable Energy Reviews, (2016). Vol. 58, pp. 796-813.E. Chica and A. Rubio-Clemente, “Design of Zero Head Turbines for Power Generation”, Renewable Hydropower Technologies Basel I. Ismail, IntechOpen, DOI: 10.5772/66907. Available from: https://www.intechopen.com/books/renewablehydropower-technologies/design-of-zero-head-turbines-forpower-generation. July 26th 2017E. Chica, J. Aguilar and A. Rubio-Clemente, “Analysis of a lift augmented hydrofoil for hydrokinetic turbines”, Renewable Energy and Power Quality Journal, (2019). Vol. 17, pp. 49-55J. Aguilar, A. Rubio-Clemente, L. Velàsquez and E. Chica. “Design and optimization of a multi-element hydrofoil for a horizontal-axis hydrokinetic turbine”, Energies, (2019), Vol. 12 (4679), pp. 1-18E. Chica, J. Aguilar and A. Rubio-Clemente, “Investigación numérica sobre el uso de álabes multi-elemento en turbina hidrocinética de eje horizontal”, Revista UIS Ingenierías, (2019). Vol. 10 (3), pp. 117-128.E. Benini, R. Ponza and A. Massaro, “High-lift multielement airfoil shape and setting optimization using multiobjective evolutionary algorithms”, Journal of Aircraft, (2011). Vol. 48(2), pp. 683-696P.M. Kumar, J. Seo, W. Seok, S.H. Rhee and A. Samad, “Multi-fidelity optimization of blade thickness parameters for a horizontal axis tidal stream turbine”, Renewable energy, (2019). Vol. 135, pp. 277-287A.I. Forrester, N.W. Bressloff and A.J. Keane, “Optimization using surrogate models and partially converged computational fluid dynamics simulations”, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, (2006). Vol 462(2071), pp. 2177-2204.R. Yondo, E. Andres and E. Valero, “A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses”, Progress in Aerospace Sciences, (2018). Vol. 96, pp. 23-61.S. Jeong, M. Murayama and K. Yamamoto, “Efficient optimization design method using kriging model”, Journal of aircraft, (2005). Vol. 42(2), pp. 413-420.J.D. Feldhacker, B.A. Jones, A. Doostan and J. Hampton, “Reduced cost mission design using surrogate models”, Advances in Space Research, (2016). Vol. 57(2), pp. 588-603V. Díaz-Casás, J.A Becerra, F. Lopez-Peña and R.J. Duro, “Wind turbine design through evolutionary algorithms based on surrogate CFD methods”, Optimization and engineering, (2013). Vol. 14(2), pp. 305-329A.D.V. Carrasco, D.J. Valles-Rosales, L.C. Mendez and M.I. Rodriguez, “A site-specific design of a fixed-pitch fixedspeed wind turbine blade for energy optimization using surrogate models”, Renewable energy, (2016). Vol. 88, pp. 112- 119.A.F. Molland, A.S Bahaj, J.R. Chaplin and W.M.J. Batten, “Measurements and predictions of forces, pressures and cavitation on 2-D sections suitable for marine current turbines”, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, (2004). Vol. 218(2), pp. 127-138P.A.S.F da Silva, L.D. Shinomiya, T.F. de Oliveira, J.R.P. Vaz, A.L.A. Mesquita and A.C.P.B. Junior, “Design of hydrokinetic turbine blades considering cavitation”, Energy Procedia, (2015). Vol. 75, pp. 277-282.N.V. Qoeipo, R.T. Haftka, W. Shyy, T. Goel, R. Vaidyanathan, and P.K. Tucker, “Surrogate-based analysis and optimization”, Progress in Aerospace Sci-ences, (2005). Vol. 41 (1), pp. 1–28A. Bhosekar and M. Ierapetritou, “Advances in surrogate based modeling, feasibility analysis, and optimization: A review”, Computers & Chemical Engineering, (2018). Vol. 108, pp. 250-267.L. Leifsson, E. Hermannsson and S. Koziel, “Optimal shape design of multi-element trawl-doors using local surrogate models”, Journal of Computational Science, (2015). Vol. 10, pp. 55-62.Y. Jin, “A comprehensive survey of fitness approximation in evolutionary computation”, Soft computing, (2005). Vol. 9(1), pp. 3-12.A.F.P. Ribeiro, A.M. Awruch and H.M. Gomes, “An airfoil optimization technique for wind turbines”, Applied Mathematical Modelling, (2012). Vol. 36(10), pp. 4898-4907.info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2ORIGINALSurrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade.pdfSurrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade.pdfapplication/pdf1369205https://dspace.tdea.edu.co/bitstream/tdea/2805/1/Surrogate%20modelling%20for%20high-lift%20multi-element%20hydrofoil%20shape%20optimization%20of%20a%20hydrokinetic%20turbine%20blade.pdf40cf4e71f6a7b6e71738f443f03c26c5MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://dspace.tdea.edu.co/bitstream/tdea/2805/2/license.txt2f9959eaf5b71fae44bbf9ec84150c7aMD52open accessTEXTSurrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade.pdf.txtSurrogate modelling for high-lift multi-element hydrofoil shape optimization of a hydrokinetic turbine blade.pdf.txtExtracted 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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.
