Shape optimization for a tube bank based on the numerical simulation and multi-objective genetic algorithm

This paper presents an optimal shape design for a tube bank in turbulent flow to enhance the thermal and hydraulic performance, where the multi-objective genetic algorithm (MOGA) and computational fluid dynamics (CFD) software is coupled in the optimization procedure. Five tubes in the tube bank could have different shapes, and twenty-five polar radii are selected as design variables accordingly. After the optimization, the initial circular tube bank is compared with two optimal solutions with the same pressure drop Delta p or the same average heat flux q. Results show that the optimal solution could increase q by 7.6% without additional flow resistance or reduce Delta p by 27% without heat transfer deterioration. Furthermore, the best compromise solution is determined by a decision-making approach, TOPSIS (technique for order preference by similarity to an ideal solution), where three different weighting factors are tested. It is found that all the selected solutions are located in the low pressure drop area, which indicates reducing the flow resistance may better improve the comprehensive performance of staggered arrangement tube banks.

Automated summary

This study presents an optimal shape design for a tube bank in turbulent flow using multi-objective genetic algorithm and computational fluid dynamics software. The results show that the optimal solution can increase heat flux by 7.6% without additional flow resistance or reduce pressure drop by 27% without heat transfer deterioration. Additionally, the best compromise solution is determined using TOPSIS method, showing that reducing flow resistance may better improve the overall performance of staggered arrangement tube banks.