Multi-objective optimization of heat transfer and flow field with different Pr numbers in cross-flow heat exchangers

 In this paper, multi-objective optimization (MOO) of heat transfer and flow field in cross-flow heat exchangers with triangular and square arrangement is performed using Computational Fluid Dynamics (CFD) techniques and Non-dominated Sorting Genetic Algorithms (NSGA II). At first, fluid flow is solved numerically in 150 various heat exchanger using CFD techniques. Finally, the CFD data will be used for Pareto based multi-objective optimization of fluid flow in cross flow heat exchanger using NSGA II algorithm. In the MOO process there are two geometrical parameters and the conflicting objective functions are to simultaneously maximize the amount of heat transfer and minimize the pressure drop. The Pareto front including optimum design variables and objective functions for two triangular and square heat exchangers are shown in results. It is shown that the achieved Pareto solution includes important design information on fluid flow in the heat exchangers.