(135f) Applications of Artificial Intelligence for Thermal Analysis of Heat Exchangers

Artificial Intelligence (AI) is gaining prominence as a technology that can be used to properly perform thermal analysis of heat exchangers with acceptable precision. In the last two decades, AI has been widely employed for the thermal analysis of heat exchangers. The applications of artificial intelligence (AI) on heat exchangers are discussed in this paper. The published investigations on the heat exchanger and thermal analysis are divided into four categories: heat exchanger modeling, estimation of heat exchanger parameters, estimation of phase change characteristics in heat exchangers, and heat exchanger control. This paper focuses on the two methods to apply artificial intelligence on heat exchangers which are the Artificial Neural Networks (ANN) and the Neuro-Fuzzy control also known as the Fuzzy Logic Controller (FLC). ANN is an information processing paradigm based on the human brain's biological neuron system. The limits of ANN for thermal analysis of heat exchangers are discussed, as well as future research needs in this sector. A fuzzy logic control model was integrated with neural network approaches. MATLAB software is used to simulate fuzzy logic controller models. Artificial Neural Network (ANN) models for simulation, optimization, and performance prediction of thermal systems incorporating heat exchangers were developed to tackle this challenge. The findings reveal that the fuzzy logic controller's control is capable of effectively stabilizing the temperature of the heat exchangers. The approach is more precise since the ANN comprises a large number of processing units in the network that execute concurrent data processing.