Abstract
Helical coil heat exchanger is used in the food industries, air cooling industries etc.., due to its advantage of structural compact and high heat transfer coefficient. Many existing researches have been carried to improve the heat transfer efficiency and pressure drop. Mathematical model of the heat exchanger has been used to validate the performance of the heat exchanger. This paper involves in review the researches related to the optimization of helical coil tube heat exchanger. Some of the optimization methods such as Taguchi method, Genetic Algorithm (GA) and Multi-Objective Genetic Algorithm (MOGA) is used. From the analysis, Artificial Neural Network (ANN) and GA method has efficient performance in modelling and optimization of heat exchanger. Although, some methods involved in economic optimization of heat exchanger and these method has lower performance.
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