Abstract

Airfoils are one of the most important factors in determining an airplane’s ability to fly. As such, their optimization holds important ramifications for the continual need to improve airplane performance. In this paper, the optimization of airfoil design is explored through numerical computational fluid dynamics. This paper first investigates the effects of Angle of Attack on airfoil lift/drag ratios, which is shown to have a significant influence on the performance of airfoils. Then, the effects from thickness are explored, and it is found that the influence of thickness is highly dependent on the specific shape of airfoil. In addition, in order to further improve airfoil aerodynamic performance, a type of modified airfoil with an additional tip is developed and simulated. The results indicate that airfoils with additional tips can perform better, but only with the proper combination of tip parameter values. For example, the modified airfoil with a tip of 0.03 L length at a 25° tip angle bested that same airfoil without an additional tip. Finally, it is found that the Backpropagation machine-learning algorithm, when trained with prior simulation data, can quickly predict lift and drag coefficients of airfoils. The results in this paper could facilitate the further optimization of airfoil design.

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