Airfoil Lift Coefficient Optimization Using Genetic Algorithm and IGP Parameterization: Volume 1

Abstract

The objective of this study is to develop a genetic algorithm that uses the IGP parameterization to increase the lift coefficient (CL) of three airfoils to be used on wings of unmanned aerial vehicles (UAVs). The geometry of three baseline airfoils was modified by developing a genetic algorithm that operates with the IGP parameterization and performs the aerodynamic analysis using XFOIL in the MATLAB environment. Subsequently, a numerical model was made for each baseline and optimized airfoil using a commercial computational fluid dynamics (CFD) code to analyze the behavior of the lift coefficient. An increase in the average CL was obtained for the Eppler 68, MH 70, and Wortmann FX 60-126 airfoils for angles of attack ranging from 0 to 10, obtaining increments of 17.243%, 14.967%, and 10.708%, respectively. Additionally, an average 5.027% uncertainty was obtained in lift coefficient calculations between XFOIL and CFD. The utility of the IGP method and genetic algorithms for parameterizing and optimizing airfoils was demonstrated. In addition, airfoils could be tailored for a specific UAV depending on the mission profile. Volume 2 of this study will include experimental data from wind tunnel.

Keywords

• CFD airfoil analysis
• airfoil genetic algorithm
• IGP airfoil parameterization
• airfoil lift coefficient
• XFOIL analysis