A comparison between the modeling of a reciprocating compressor using artificial neural network and physical model
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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http://dx.doi.org/10.1016/j.ijrefrig.2015.07.017 |
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Título
A comparison between the modeling of a reciprocating compressor using artificial neural network and physical modelFecha de publicación
2015Editor
ElsevierCita bibliográfica
BELMAN-FLORES, J. M., et al. A comparison between the modeling of a reciprocating compressor using artificial neural network and physical model. International Journal of Refrigeration, 2015, vol. 59, p. 144-156.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0140700715002248Palabras clave / Materias
Resumen
This article presents the development, validation, and comparison of two methods for modeling a reciprocating compressor. Initially, the physical mode is based on eight internal sub-processes that incorporate infini ... [+]
This article presents the development, validation, and comparison of two methods for modeling a reciprocating compressor. Initially, the physical mode is based on eight internal sub-processes that incorporate infinitesimal displacements according to the piston movement. Next, the analysis and modeling of the compressor through the application of artificial neural networks are presented. The input variables are: suction pressure, suction temperature, discharge pressure, and compressor rotation speed. The output parameters are: refrigerant mass flow rate, discharge temperature, and energy consumption. Both models are validated with experimental data for the refrigerants R1234yf and R134a; computer simulations show that mean relative errors are below ±10% with the physical model, and below ±1% when artificial neural networks are used. Additionally, the performance of the models is evaluated through the computation of the squared absolute error. Finally, these models are used to compute an energy comparison between both refrigerants. [-]
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International Journal of Refrigeration, 2015, vol. 59, p.Derechos de acceso
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/restrictedAccess
info:eu-repo/semantics/restrictedAccess
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