Artificial Neural Network Involved in the Action of Optimum Mixed Refrigerant (Domestic Refrigerator) (TECHNICAL NOTE)

Abstract

This analysis principally focuses on the implementation of Radial basis function (RBF) and back propagation (BPA) algorithms for training artificial neural network (ANN) to get the optimum mixture of Hydro fluorocarbon (HFC) and organic compound (Hydrocarbons) for obtaining higher coefficient of Performances (COPs). The thermodynamical properties of mixed refrigerants are observed using REFPROP 9 software system that contains details of refrigerants. Totally different mixtures of the refrigerants along with their COP are obtained by the REFPROP 9. This task consumes time in getting the right combination of refrigerants as lot of menu choices have to be compelled to be chosen within the REFPROP 9. In order to form the method of checking out the correct mixed refrigerants with minimum manual intervention, RBF is trained and tested with the different patterns of mixed refrigerants. The RBF / BPA mixed refrigerant analysis software has been developed by using MATLAB 11a.