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COP PREDICTION BY THE INTEGRATION OF A WATER PURIFICATION SYSTEM TO A HEAT TRANSFORMER

DOI: 10.1615/IHTC13.p22.170
10 pages




J. Alfredo Hernandez
Centro de Investigación en Ingenieria y Ciencias Aplicadas (CIICAp) - Universidad Autónoma del Estado de Morelos, Morelos, México

Y. Morales
Autonomous University of Morelos State (UAEM), Cuernavaca, México

L. I. Morales
Autonomous University of Morelos State (UAEM), Cuernavaca, México

J. Siqueiros
Autonomous University of Morelos State (UAEM), Cuernavaca, México

D. Juarez
Autonomous University of Morelos State (UAEM), Cuernavaca, México

Sinopsis

A predictive model for a water purification process thermal integrated to an absorption heat transformer, using artificial neural network, is proposed in order to obtain on-line predictions of increased COP. This model takes into account the input and output temperatures for each one of the four components (absorber, generator, evaporator, and condenser), as well as two pressure parameters of the absorption heat transformer and LiBr+H2O concentrations. A feedforward network with one hidden layer was used to predict the COP values which increased with energy recycling from auxiliary condenser. For the network, the Levenberg-Marquardt learning algorithm, the hyperbolic tangent sigmoid transfer-function and the linear transfer-function were used. The best fitting training data set was obtained with three neurons in the hidden layer, which made it possible to predict COP with accuracy at least as good as that of the experimental error, over the whole experimental range. On the validation data set, simulations and experimental data test were in good agreement (r2>0.99). The developed models can be used for a reliable on-line state estimation and control of water purification process integrated to an absorption heat transformer.

IHTC-13 Digital Library

Measurement of fluid temperature with an arrangement of three thermocouples FLOW BOILING OF A HIGHLY VISCOUS POLYMER SOLUTION