Performance Analysis of CO2/NH3 Cascade Refrigeration System Using ANNs

In this study, artificial neural networks (ANNs) have been used for performance analysis of a CO2/NH3 cascade refrigeration system using a data set, obtained from a thermodynamic model implemented in EES. Thermodynamic parameters of the system are estimated in terms of condensing temperature of ammonia, evaporating temperature of carbon dioxide, condensing temperature of carbon dioxide and temperature difference in cascade condenser. The computer program has been performed under MATLAB environment using neural network toolbox. New formulation obtained from ANN for this couple of refrigerants is presented for the calculation of target values. The total R value obtained when unknown data were used to the networks was 0.999992 which is very satisfactory. It can be used where a very accurate and fast estimation, simulation or optimization of the system performance is of interest to engineers.

Ammonia, Carbon dioxide, Cascade refrigeration system, Neural Networks