Artificial Neural Network Analysis of the Thermal Performance of a Plate Heat Exchanger - Arisariyawong, Tanayos (Srinakharinwirot University Engineering Journal, 2019)
This paper proposes the use of artificial neural network (ANN) for the effectiveness and overall heat transfer coefficient using water as working fluid. The experiments are performed using the average inlet hot water temperature between 40 – 50 oC, the average inlet cold water temperature between 20 – 30 oC, the average mass flow rate of hot water between 0.0273 - 0.0444 kg/s and the average mass flow rate of hot water is 0.0196 kg/s. For the ANN model, a single hidden layer structure is chosen and various learning algorithms are applied to adjust errors for obtaining the optimal ANN model. From the experimental results show that the 5 hidden neurons and Levenberg-Marquardt backpropagation learning algorithms is the optimal ANN model. The predicted results are verified with the experimental data and gives R = 0.99631, 0.98469 for effectiveness and overall heat transfer coefficient, respectively.