A strategy for helical coils multi-objective optimization using differential evolution algorithm based on entropy generation theory

Abstract

The optimization of helical coils heat transfer can be solved as a mathematical problem. Firstly, this study proposed a strategy of optimal design applied to helical coils based on differential evolution (DE) algorithm. Secondly, the changes of Nusselt number (Nu), pressure drop per unit length (f′), and modified entropy generation number (Ns′) were investigated numerically, and the multi-objective optimization model was established to optimize design parameters, including the Reynolds number (Re), coil diameter (D), and coil pitch (H), of helical coiled tubes. The optimum results obtained by differential evolution were compared with genetic algorithm (GA). Finally, the strategy using differential evolution was applied to a helical coils heat exchanger (HCHEX) optimum design and good results are obtained. The results show that: Ns′ is most obviously affected by the change of H, followed by D, and Re has little influence on it; When using Ns′ minimization for heat transfer optimization, attention should be paid to its scope of application, in this paper, the performance of helical coils has been improved after optimization; Using differential evolution not only converges faster than using genetic algorithm, but also get better global optimal solutions.