Aerodynamics Analysis Comparison between NACA 4412 and Falco Air foils

Abstract

This article presents a comparison between the NACA 4412 airfoil and Falco airfoils. The focus is on conducting a comprehensive analysis of the geometries of the Falco UAV and NACA 4412 airfoil, as the shape of the airfoil plays a crucial role in determining lift and drag forces. A two-dimensional computational fluid dynamics (CFD) investigation was conducted utilizing the conventional k-epsilon model to assess the turbulence effects resulting from high airflow rates around the airfoil. The study examined the behavior of numerical streamlines around the two distinct geometries across a range of angles of attack from 0 to 120 degrees.To identify the optimal airfoil shape for unmanned aerial vehicles (UAVs), the stress distribution, velocity distribution, and coefficients of aerodynamic forces are computed at various angles of attack. This analysis aims to determine the airfoil shape that yields the most favorable results for UAV applications.

A comparative study of various airfoils was conducted to assess their suitability for engineering applications such as drones, and the Falco airfoil emerged as a promising candidate due to its superior lift-to-drag ratio. The study employed the computational simulation software ANSYS Fluent, which utilized Navier-Stokes and energy equations to predict the flow pattern around different airfoils. The Falco UAV airfoil demonstrated exceptional performance in terms of lift coefficient and lift-to-drag ratio, while maintaining an acceptable drag coefficient. In contrast to other airfoils with identical drag coefficients, the Falco UAV airfoil exhibited a significantly higher lift-to-drag ratio. The aerodynamic performance was greatly influenced by the angle of attack, with the most favorable outcomes observed at an angle of 12°. As the angle of attack increased, the areas of low pressure and weak flow progressively shifted from the lower surface to the upper surface, indicating a change in flow separation from the bottom to the top. It has been demonstrated that computational modeling using FLUENT yields results comparable to those obtained in a wind tunnel, providing both accuracy and cost savings by eliminating the need for extensive experimentation.