Experimental and Numerical Optimization Study on an Airfoil-Shaped Heat Exchanger

Heat exchanger design is a laborious and time-consuming task that often relies on a trial-and-error process. In light of this, our study proposes a design method for optimizing airfoil-shaped heat exchangers using the improved stochastic ranking evolutionary strategy (ISRES) algorithm. The ISRES algorithm provides significant advantages in identifying the global optimum, surpassing genetic algorithms (GAs). In the present study, the thermal model of the heat exchanger protype was validated using experimental techniques. Additionally, the ISRES algorithm was employed for the optimization of a plate-fin heat exchanger with airfoil-shaped fins by minimizing the total heat transfer area and pressure drops, while considering the main geometrical parameters of the exchanger as the design variables. The corresponding computer code was developed, and two case studies were conducted. In case study 1, the total heat transfer area was saved up to 25.7%, while in case study 2, the objective function value reached its minimum value of 0.0738. The numerical results demonstrate that the ISRES algorithm can be successfully applied in optimizing heat exchangers. Finally, a parametric analysis was conducted to evaluate the sensitivity of the proposed method to the heat transfer area.