Multi-objective shape optimization of a plate-fin heat exchanger using CFD and multi-objective genetic algorithm

A theoretical optimization was carried out to develop a plate-fin heat exchanger for the hydraulic retarder. CFD simulation and multi-objective optimization were combined to improve the performances of the original heat exchanger, which could not be applied to the practical engineering application. The optimizations of the Colburn factor j and the friction factor f were treated as the multi-objective optimization problem due to the presence of two conflicting objectives. The second generation Non-Dominated Sorting Genetic Algorithm (NSGA-II) was employed to optimize the shape of the heat exchanger. The optimization results indicated that the Colburn factor j increased by 12.83% and the friction factor f decreased by 26.91%, which showed that the convective heat transfer was enhanced and the flow resistance was also significantly reduced. Then, internal flow fields involving temperature, pressure and velocity were qualitatively compared to further emphasize the optimization effect. Finally, the field synergy numbers were compared and analyzed, which could help to prove the rationality of the optimized result and guide the following design or optimization tasks.