Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks
This work presents a discussion on pressure drop of R-407C during two-phase flows, and the application of artificial neural network (ANN) to predict these pressure drops in a smooth copper tube, for 4.5 mm and 8.0 mm inner diameter. The ANN was trained using data from 127 experiments encountered in...
- Autores:
-
Garcia, Juan Jose
Garcia, Franklin
Bermúdez, José
Machado, Luiz
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Francisco de Paula Santander
- Repositorio:
- Repositorio Digital UFPS
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.ufps.edu.co:ufps/1349
- Acceso en línea:
- http://repositorio.ufps.edu.co/handle/ufps/1349
https://doi.org/10.1016/j.ijrefrig.2017.10.007
- Palabra clave:
- R407C
Evaporation
Artificial network neural
Pressure drop
Smooth horizontal tubes
- Rights
- openAccess
- License
- © 2017 Elsevier Ltd and IIR. All rights reserved.
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Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks |
| title |
Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks |
| spellingShingle |
Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks R407C Evaporation Artificial network neural Pressure drop Smooth horizontal tubes |
| title_short |
Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks |
| title_full |
Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks |
| title_fullStr |
Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks |
| title_full_unstemmed |
Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks |
| title_sort |
Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks |
| dc.creator.fl_str_mv |
Garcia, Juan Jose Garcia, Franklin Bermúdez, José Machado, Luiz |
| dc.contributor.author.none.fl_str_mv |
Garcia, Juan Jose Garcia, Franklin Bermúdez, José Machado, Luiz |
| dc.subject.proposal.eng.fl_str_mv |
R407C Evaporation Artificial network neural Pressure drop Smooth horizontal tubes |
| topic |
R407C Evaporation Artificial network neural Pressure drop Smooth horizontal tubes |
| description |
This work presents a discussion on pressure drop of R-407C during two-phase flows, and the application of artificial neural network (ANN) to predict these pressure drops in a smooth copper tube, for 4.5 mm and 8.0 mm inner diameter. The ANN was trained using data from 127 experiments encountered in the literature. Diameter, mass flux, saturation pressure and local vapor quality were used as inputs, whereas the pressure drop was considered as output. The number of neurons and hidden layers were determined based on the accuracy of results. The trained ANN was able to estimate the experimental data with a MAPE (Mean Absolute Percentage Error) of 6.11%, and a correlation coefficient (R) of 0.999 for all data, using a configuration with 14 neurons in the hidden layer. The obtained results were within ±10% for 90% of all data, and ±30% for 99% of all data. Compared to the well established literature correlations for pressure drop, the ANN demonstrates how important this tool is to predict pressure drop accurately. |
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2018 |
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2018-01 |
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2021-11-24T15:56:29Z |
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2021-11-24T15:56:29Z |
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Artículo de revista |
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https://doi.org/10.1016/j.ijrefrig.2017.10.007 |
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eng |
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eng |
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International Journal of Refrigeration |
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Vol.85 (2018) |
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302 |
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(2018) |
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Garcia, J. J., Garcia, F., Bermúdez, J., & Machado, L. (2018). Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks. International Journal of Refrigeration, 85, 292-302. |
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International Journal of Refrigeration |
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© 2017 Elsevier Ltd and IIR. All rights reserved. |
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http://purl.org/coar/access_right/c_abf2 |
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info:eu-repo/semantics/openAccess |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) |
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© 2017 Elsevier Ltd and IIR. All rights reserved. Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) http://purl.org/coar/access_right/c_abf2 |
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32 páginas |
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International Journal of Refrigeration |
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Reino Unido |
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Garcia, Juan Josebe0a6b2f0fd9a5d9adc552bdf1e12040Garcia, Franklindddd8a3b5dcbccd624ae608f823ebfdcBermúdez, José6d44da96cb20bd56290d5e13f43bd815Machado, Luiz11bf0bc2c2b19ffe4c2712fe2e0d21ff2021-11-24T15:56:29Z2021-11-24T15:56:29Z2018-01http://repositorio.ufps.edu.co/handle/ufps/1349https://doi.org/10.1016/j.ijrefrig.2017.10.007This work presents a discussion on pressure drop of R-407C during two-phase flows, and the application of artificial neural network (ANN) to predict these pressure drops in a smooth copper tube, for 4.5 mm and 8.0 mm inner diameter. The ANN was trained using data from 127 experiments encountered in the literature. Diameter, mass flux, saturation pressure and local vapor quality were used as inputs, whereas the pressure drop was considered as output. The number of neurons and hidden layers were determined based on the accuracy of results. The trained ANN was able to estimate the experimental data with a MAPE (Mean Absolute Percentage Error) of 6.11%, and a correlation coefficient (R) of 0.999 for all data, using a configuration with 14 neurons in the hidden layer. The obtained results were within ±10% for 90% of all data, and ±30% for 99% of all data. Compared to the well established literature correlations for pressure drop, the ANN demonstrates how important this tool is to predict pressure drop accurately.32 páginasapplication/pdfengInternational Journal of RefrigerationReino UnidoInternational Journal of RefrigerationVol.85 (2018)302(2018)29285Garcia, J. J., Garcia, F., Bermúdez, J., & Machado, L. (2018). Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks. International Journal of Refrigeration, 85, 292-302.International Journal of Refrigeration© 2017 Elsevier Ltd and IIR. All rights reserved.info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2https://www.sciencedirect.com/science/article/abs/pii/S0140700717303912Prediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networksArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://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_970fb48d4fbd8a85R407CEvaporationArtificial network neuralPressure dropSmooth horizontal tubesAkdag, U., Komur, M.A., Akcay, S., 2016. Prediction of heat transfer on a flat plate subjected to a transversely pulsating jet using artificial neural networks. Applied Thermal Engineering 100, 412-420. http://dx.doi.org/10.1016/j.applthermaleng.2016.01.147.Andrzejczyk, R., Muszynski, T., Dorao, C.A., 2017. Experimental investigations on adiabatic frictional pressure drops of R134a during flow in 5 mm diameter channel. Experimental Thermal and Fluid Science 83, 78-87. https://doi.org/10.1016/j.expthermflusci.2016.12.016Aprea, C., Greco, A., Maiorino, A., 2017. An application of the artificial neural network to optimise the energy performances of a magnetic refrigerator. International Journal of Refrigeration 82, 238-251. http://dx.doi.org/10.1016/j.ijrefrig.2017.06.015.Aprea, C., Greco, A., Rosato, A., 2008. Comparison of R407C and R417A heat transfer coefficients and pressure drops during flow boiling in a horizontal smooth tube. Energy Conversion and Management 49, 1629-1636. https://doi.org/10.1016/j.enconman.2007.11.003.Avcı, H., Kumlutaş, D., Özer, Ö., Özşen, M., 2016. Optimisation of the design parameters of a domestic refrigerator using CFD and artificial neural networks. 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International Journal of Refrigeration 80, 130-144. http://dx.doi.org/10.1016/j.ijrefrig.2017.04.025.LICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://repositorio.ufps.edu.co/bitstream/ufps/1349/2/license.txt2f9959eaf5b71fae44bbf9ec84150c7aMD52open accessORIGINALPrediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks.pdfPrediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks.pdfapplication/pdf1713025https://repositorio.ufps.edu.co/bitstream/ufps/1349/1/Prediction%20of%20pressure%20drop%20during%20evaporation%20of%20R407C%20in%20horizontal%20tubes%20using%20artificial%20neural%20networks.pdfd4b1fc36dd06c2d89c98a41f78003280MD51metadata only accessTEXTPrediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks.pdf.txtPrediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks.pdf.txtExtracted texttext/plain45114https://repositorio.ufps.edu.co/bitstream/ufps/1349/3/Prediction%20of%20pressure%20drop%20during%20evaporation%20of%20R407C%20in%20horizontal%20tubes%20using%20artificial%20neural%20networks.pdf.txt7e75364d830a69c81d8808de8194a77fMD53metadata only accessTHUMBNAILPrediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks.pdf.jpgPrediction of pressure drop during evaporation of R407C in horizontal tubes using artificial neural networks.pdf.jpgGenerated Thumbnailimage/jpeg7837https://repositorio.ufps.edu.co/bitstream/ufps/1349/4/Prediction%20of%20pressure%20drop%20during%20evaporation%20of%20R407C%20in%20horizontal%20tubes%20using%20artificial%20neural%20networks.pdf.jpg28713dccc6e9bddc9e2c98788139b39dMD54metadata only accessufps/1349oai:repositorio.ufps.edu.co:ufps/13492022-05-23 10:47:26.012metadata only accessRepositorio Universidad Francisco de Paula 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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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