Energy and exergy analysis of LiBr-H2O-operated vapour absorption refrigeration system using the ANN approach

Abstract

In this work, computational intelligence is used to calculate the energy and exergy analysis of lithium bromide–water (LiBr-H2O)-operated vapour absorption refrigeration system. An artificial neural network (ANN) is trained for predicting the thermodynamic properties of the solutions. Mathematical equations are extracted from the trained and validated ANN for predicting the same. Coefficient of multiple determination (R 2) is calculated equal to the unity for test dataset of both thermodynamic properties which justified the use of artificial intelligence. The use of the extracted mathematical expressions can be leveraged with any programming language for estimating specific enthalpy and specific entropy of the working fluid, as described in this work. Results of energy and exergy analysis are compared with the published literature work.