6/22/2023 0 Comments Low speed airfoil![]() ![]() ![]() The airfoil is successfully optimized using the GA with the final result of a reduced drag coefficient by almost 50%, and a set of optimum solutions with varying trade-off for each objective is obtained from the multi-objective case. The UIUC Airfoil Data Site includes airfoil coordinates for approximately 1,600. UIUC LSATs airfoil data from Volumes 1-4, and 6 are here. Volume 4 was published as a NREL report that includes many wind turbine airfoils at low Reynolds numbers. 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. Summary of Low-Speed Airfoil Data - Volumes 1,2, 3, 4, and 5 are available. ![]() Airfoils for high-speed aircraft, especially for supersonic flight, are much thinner with pointed leading edges and use less camber. In this paper, to achieve an optimum shape configuration, a methodology based on an evolutionary algorithm is proposed. From a random initial population, GA will generate new individuals iteratively until a desired solution is found. For example, airfoils for use on the wings of low-speed airplanes are generally thicker (in terms of their thickness-to-chord ratio) and have more curvature or camber. The algorithm mimics the concept of genetic inheritance and Darwinian natural selection in living organisms. 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. ![]()
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