![]() ![]() To validate the proposed algorithm, the study compared it with a previous flow solver for the same airfoil. These bounds can be adjusted (depending on the capabilities of the airfoils). As an innovation in the algorithm, bounds were defined for the shape change during optimization so that the result can be constructed within the capabilities of the morphing wing. However, morphing airfoils have certain deformation limitations. The optimal shape was found using the proposed algorithm by defining one NACA profile as the initial value and another NACA profile as the limit for the optimized shape, considering the aerodynamic coefficients and flight conditions. The study used NACA-4 digit airfoils as input for the initial assumption and the range of shape change. ![]() ![]() From an aerodynamic perspective, the development of shape geometry is a crucial step in airfoil development. The proposed algorithm can be understood as an optimization method, which employs the adjoint method, a powerful tool for estimating the sensitivity of the model output to the input in numerous studies. Therefore, in this study, we propose an algorithm that is capable of robustly optimizing the shape of the airfoil based on variable parameters of the airfoil and flight conditions. The introduction of flexible airfoils has allowed the shape of the airfoil to vary, depending on the flight conditions. Optimizing the aerodynamic shape of an airfoil is a critical concern in the aviation industry. ![]()
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