Multi-objective optimization of a double helical coil heat exchanger using response surface method and genetic algorithm.

The double helix coil heat exchanger, which has high heat transfer performance, has been increasingly used in heat transfer systems. In this paper, a 3D numerical model is established to simulate heat transfer performance of the double helical coil. Then, the Box-Behnken design method and response surface method (RSM) are used to establish response surface models of the input parameters (internal coil pitch, external coil pitch, internal helix diameter, external helix diameter, and coil diameter), which are used to evaluate the interaction of input parameters and objective functions (overall heat transfer coefficient and pressure drop). Finally, the multi-objective genetic algorithm (MOGA) is used to optimize the design parameters of double helix coil heat exchangers, and the optimized double helix coil heat exchanger with high heat transfer coefficient, low exergy loss and pressure drop are obtained. Compared with the original design, the pressure drop decreases by 19.98 %, the exergy loss decreases by 8.7 %, and the overall heat transfer coefficient increases by 5.34 %. • BBD method and RSM are adopted to establish the prediction model for double helix coil heat exchangers performance. • MOGA is used to optimize the design parameters of double helix coil heat exchangers. • An optimized double helix coil heat exchanger with high heat transfer coefficient, pressure drop performance is obtained. [ABSTRACT FROM AUTHOR]