Coefficent of performance prediction by a polynomial model of absorption heat transformer
Predicción del coeficiente de desempeño por un modelo polinomial para un transformador térmico
B.A. Escobedo-Trujillo1, F.A. Alaffita-Hernández1, D. Colorado2* and J. Siqueiros3
1 Facultad de Ingeniería, Universidad Veracruzana. Campus Coatzacoalcos, Av. Universidad km 7.5 Col. Santa Isabel, C.P. 96535, Coatzacoalcos, Veracruz, México.
2 Centro de Investigación en Recursos Energéticos y Sustentables. Universidad Veracruzana. Av. Universidad km 7.5 (Col. Santa Isabel,) C.P. 996535, Coatzacoalcos, Veracruz, México. * Corresponding author. E-mail: dcolorado@uv.mx Tel.52(921) 203 6516.
]]> 3 Secretaría de Innovación, Ciencia y Tecnología, Av. Atlacomulco no. 133, esq. Calle de la ronda, Col. Acapantzingo, Cuernavaca, Morelos, C.P. 62440.
Received March 16, 2014.
Accepted June 25, 2014.
Abstract
A polynomial model is developed to predict the coefficient of performance of a water purification process integrated to an absorption heat transformer. The range of the coefficient of performance operations was from 0.21 to 0.39. This model used: inlet temperature in the generator which comes from the absorber, outlet temperature in the absorber that comes from the generator, inlet temperature in the absorber that comes from the generator, water-lithium bromide solution inlet concentration in the generator that comes from the absorber and the pressure in the absorber and generator. A polynomial model is presented in order to obtain coefficient of performance prediction with a determination coefficient of 0.91919. Level surfaces of the coefficient of performance against the inlet variables for the polynomial model and residual analysis were presented with the aim of validating the model. This work has the purpose of providing faster and simpler solutions instead of the complex equations used for the analysis of the heat transformer in order to obtain accurate coefficient of performance prediction. The operation variable with the greater contribution of determination coefficient is presented.
Keywords: lithium bromide solution, residual analysis, Gaussian distribution, water purification.
Resumen
]]> Un modelo polinomial es desarrollado para predecir el coeficiente de desempeño para un sistema de purificación de agua integrado a un transformador térmico. El rango de operación del coeficiente de desempeño fue desde 0.21 a 0.39. El modelo usa: temperatura de entrada en el generador el cual proviene del absorbedor, temperatura de salida en el absorbedor el cual proviene del generador, temperatura de entrada en el absorbedor el cual proviene del generador, concentración de entrada de la solución de bromuro de litio en el generador proveniente del absorbedor y la presión en el absorbedor y generador. Un modelo polinomial es presentado con el objetivo de predecir el coeficiente de desempeño con un coeficiente de determinación de 0.9919. Superficies de nivel del coeficiente de desempeño contra las variables de entrada del modelo polinomial y el análisis residual son presentados con el objetivo de validar el modelo. Este trabajo tiene el objetivo de proveer una solución rápida y simple en lugar de ecuaciones complejas usadas en el análisis del transformador térmico con el objetivo de obtener apropiadas predicciones del coeficiente de desempeño. La variable de operación con la mayor contribución en el coeficiente de determinación es presentada.Palabras clave: solución de bromuro de litio, análisis residual, distribución Gaussiana, purificación de agua.
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References
Castilla M, Álvarez JD, Ortega MG, Arahal MR. (2013) Neural network and polynomial approximated thermal comfort models for HVAC systems. Building and Environment, 59:107-115. [ Links ]
Colorado D, Santoyo-Castelazo E, Hernández JA, García-Valladares O, Siqueiros J, Juárez D. (2009) Heat transfer of a helical double-pipe vertical evaporator: Theoretical analysis and experimental validation. Applied Energy, 86:1144-1153. [ Links ]
]]>Colorado D, Hernández JA, García-Valladares O, Huicochea A, Siqueiros J. (2011) Numerical simulation and experimental validation of a helical double-pipe vertical condenser. Applied Energy, 88:2136-2145. [ Links ]
Devore J. (2004) Probability and statistics for engineering and the sciences. Thomson Learning, Inc. 6th. edition, Canada. [ Links ]
Flores O, Velaízquez V, Meza M, Horacio H, Juaírez D, Hernaíndez JA. (2013) Estimation of the condensation heat transfer coefficient for steam water at low pressure in a coiled double tube condenser integrated to a heat transformer. Revista Mexicana de Ingeniería Química, 12:303-313. [ Links ]
Hernández JA, Juárez-Romero D, Morales LI, Siqueiros J. (2008) COP prediction for the integration of a water purification process in a heat transformer: with and without energy recycling. Desalination, 219:66-88. [ Links ]
Hernández JA, Bassam A, Siqueiros J, Juárez-Romero D. (2009) Optimum operating conditions for a water purification process integrated to a heat transformer with energy recycling using neural network inverse. Renewable Energy, 34:1084-1091. [ Links ]
]]>Horuz I, Kurt B. (2009) Single stage and double absorption heat transformers in an industrial application. International Journal of Energy Research, 33:787-798. [ Links ]
Hossain Khan A, Muntasir T, Zahidur Rahman ASM, Kumar Acharjee UK, Abu layek A. (2011) Multiple polynomial regression for modeling a MOSFET in saturation to validate the early voltage. IEEE symposium on industrial electronics and applications, 261-266. [ Links ]
Juárez D, Shah N, Pliego-Solorzano F, Hernandez JA, Siqueiros J, Huicochea A. (2009) Heat and mass transfer in a horizontal pipe absorber for a heat transformer. Desalination and water treatment, 10:238?244. [ Links ]
Mavromatidis LE, Bykalyuk A, Lequay H. (2013) Development of polynomial regression models for composite dynamic envelopes thermal performance forecasting. Applied Energy, 104:379?391. [ Links ]
Montgomery D., Peck E, Geoffrey V. (2001) Introduction to linear regression analysis. Wiley series in Probability and Statistics. 3th edition, USA. [ Links ]
]]>Montgomery D., Runger G. (2010) Probabilidad y estadíística aplicadas a la ingenieríía. LIMUSA. 2do. edition, USA. [ Links ]
Morales-Gómez LI. (2005) Estudio experimental sobre un sistema portatil de purificación de agua integrado a un transformador térmico, M. S. Thesis. México. CIICAP-UAEM. [ Links ]
Pérez-González A, Vilar-Fernández JM, González-Manteiga W. (2009) Asymptotic properties of local polynomial regression with missing data and correlated errors. Annals of the Institute of Statistical Mathematics, 61:85-109. [ Links ]
Rivera W, Romero RJ. (1998) Thermodynamic design data for absorption heat transformers. part seven: operating on an aqueous ternary hydroxide. Applied Thermal Engineering, 18(3-4):147?56. [ Links ]
Rivera W, Cerezo J, Rivero R, Cervantes J, Best R. (2003) Single stage and double absorption heat transformers used to recover energy in a distillation column of butane and pentane. International Journal of Energy Research, 27:1279-1292. [ Links ]
]]>Rivera W, Huicochea A, Martínez H, Siqueiros J, Juárez D, Cadenas E. (2011) Exergy analysis of an experimental heat transformer for water purification. Energy, 36:320-327. [ Links ]
Sekar S, Saravanan R. (2011) Experimental studies on absorption heat transformer coupled distillation system. Desalination, 274:292-301. [ Links ]
Sencan A, Kizilkan O, Bezir NC, Kalogirou S. (2007) Different methods for modeling absorption heat transformer powered by solar pond. Energy Conversion and Management, 48:724?735. [ Links ]
Siqueiros J, Romero RJ. (2007) Increase of COP for heat transformer in water purification systems. Part I ? Increasing heat source temperature. Applied Thermal Engineering, 27:1043?1053. [ Links ]
Sozen A, Serdar-Yucesu H. (2007) Performance improvement of absorption heat transformer. Renewable Energy, 32:267-284. [ Links ]
]]>Torres-Merino J. (1997) Contacteurs gaz-liquide pour pompes á chaleur á absorption multi-étagées, Ph. D. thesis France. Inst Natl Polytechnique de Lorraine. [ Links ]
]]>