Shape optimization of cambered airfoils using a genetic algorithm and a multipoint inverse method

This thesis presents a process to optimize a cambered airfoil with the MATLAB genetic algorithm (GA) and a multipoint inverse method called PROFOIL. XFOIL was used to evaluate the aerodynamic performance of each airfoil. Data processing techniques and a custom penalty function were developed in order to overcome challenges in integrating these tools. The viability of this approach was assessed in three airfoil optimization studies. First, the optimizer was tuned using a parameterized study of various GA configurations for optimizing the (Cl/Cd)max for an 18% thick airfoil at the design conditions: Cm = -0.063 at Re = 6.88 * 10^6 and Cm = -0.030 at Re = 2.00 * 10^6. The first is a typical flow condition for a wind turbine at the r/R = 0.75 blade section location, and the second is identical to the requirements used in designing the Liebeck L1003. This tuned GA was used for the rest of the thesis. In the second study, the optimization of (Cl/Cd)max for an 18% thick airfoil with design Cm = -0.060 was conducted at Re = 6.00 * 10^6, which is a typical condition for general aviation aircraft. It was observed that the optimized airfoil resembles the Liebeck L1003 airfoil, which was designed with a Stratford pressure recovery distribution. In the third study, a series of Clmax optimization runs was performed for varying pitching moments at Re = 6.00 * 10^6, revealing final solutions that segregated into two types of airfoils that differ in camber. It was shown that the optimizer converged on reflexed airfoils for design coefficients of moment Cm = 0.000 through Cm = -0.050 and on aft-loaded airfoils for Cm = -0.075 through Cm = -0.200. In addition, both groupings of airfoils exhibited an increase in Clmax concomitant with increasing nose-down pitching moment. The results indicate that this approach can reproduce airfoils designed with central design philosophies using only a limited number of design inputs