The objective is to minimize the coefficient of drag from a low-speed airfoil of NACA 0012 using PARSEC parameterization technique and a low-fidelity CFD solver XFOIL, with an addition of minimizing the absolute value of coefficient of moment for multi-objective optimization problem. If you are a serious builder of radio controlled sailplanes or drones. From a random initial population, GA will generate new individuals iteratively until a desired solution is found. Performance data for low reynolds numbers airfoils. There are many types of airfoils, such as low-speed airfoils, supercritical airfoils, and natural laminar flow airfoils 3,4. The characteristics of the airfoil strongly affect the performance of the aerodynamic parts, which influence on the energy cost of the machine. The algorithm mimics the concept of genetic inheritance and Darwinian natural selection in living organisms. An airfoil is a basic element of wing, wind turbine, and turbomachinery.

The following research presents an airfoil optimization using gradient-free technique called genetic algorithm (GA).

Objectives of such optimization problem usually involve black-box function of computational simulation, which will not fit the use of conventional gradient-based optimization method as it needs information of derivatives that only well-defined functions are able to provide. Aerodynamic optimization is undoubtedly an important part of design due to its effect on an aircraft’s performance.

Low speed airfoil