The performance on the air side flow is often limited due to its lower heat transfer coefficient. This work is related to numerical simulation to study the significance of employing delta winglets in flat finned and wavy finned-tube heat exchangers. For this purpose, three-dimensional simulation data and a multi-objective genetic algorithm are employed. The angle of attack (α) of delta winglets and Reynolds number varied from 15° to 75° and 500 to 1300, respectively.
Employing delta winglets has increased the heat transfer per unit temperature and per unit volume (Z) and the fan power per unit core volume (E) for both flat finned and wavy finned-tube heat exchangers. To achieve a maximum heat transfer enhancement and a minimum friction factor, the optimal values of these parameters (Re and α) are calculated using the Pareto optimal strategy. For this purpose, CFD data, a surrogate model (neural network) and a multi-objective optimization genetic algorithm are combined. Results show that the performance of wavy finned-tube heat exchangers is higher than flat-finned tube heat exchangers which signify the importance of delta winglets in the wavy finned-tube heat exchangers.