Effect of plasma excitation on aerodynamic characteristics of airfoil under Martian conditions

Authors

  • Yang Hongkong
  • Gao Yongxin
  • Wang Zhongming
  • Li Yiwen
  • Yao Cheng

DOI:

https://doi.org/10.59782/aai.v1i3.316

Keywords:

Mars UAV, low Reynolds number, plasma excitation, lift increase, drag reduction

Abstract

Due to the low density and pressure of the Martian atmosphere, the aerodynamic performance of the airfoil of the Mars UAV needs to be further improved. Plasma excitation active flow control technology is used to improve the lift of the airfoil and reduce the drag of the airfoil under Martian conditions. The effects of the action position, excitation power and incoming flow angle of attack on the lift and drag of the airfoil are studied under the low Reynolds number conditions on Mars. The results show that plasma excitation increases lift in the trailing edge area of the lower surface, with a maximum lift increase rate 37%; reduces drag in the leading edge area of the lower surface, with a maximum drag reduction rate 8%; the greater the excitation power and the smaller the incoming flow angle of attack, the more obvious the improvement of the airfoil lift-to-drag ratio. Plasma excitation induces pressure waves, forming a pressurization zone and a decompression zone upstream and downstream of the excitation, respectively, resulting in the formation of a pressurization surface and a decompression surface on the airfoil surface. When the excitation position is close to the trailing edge, the pressurization surface expands, and the pressure difference between the upper and lower surfaces of the airfoil increases, thereby achieving lift increase; when the excitation position is close to the leading edge, the decompression surface expands, and the pressure difference drag of the airfoil decreases, thereby achieving drag reduction.

How to Cite

Hongkong, Y., Yongxin, G., Zhongming, W., Yiwen, L., & Cheng, Y. (2024). Effect of plasma excitation on aerodynamic characteristics of airfoil under Martian conditions. Journal of Applied Artificial Intelligence, 1(3), 50–64. https://doi.org/10.59782/aai.v1i3.316

Issue

Section

Articles