Exergy analysis of flue gases and modeling with artificial neural networks

In this study, flue gases from natural gas-fired industrial furnaces were thermodynamically investigated. in the analysis, the experimentally measured values of concentration of the flue gas components, i.e. o2, co2, h2o and n2, the flue gas temperature and the flue gas outlet rate were used. the usable amount of energy (exergy) released to the environment by flue gases in terms of different output parameters was calculated, then effects of physical and chemical properties of flue gases on the exergy losses were investigated. in addition, the calculated exergy data were modeled by artificial neural network (ann) method, besides that ann model with best accuracy was determined by altering the number of neurons in the hidden layer. with the help of ann model as well as concentration, temperature and rate of flue gases, it has been shown that the exergy of flue gases value can be estimated with high accuracy.