Cessna 172 G1000 Aircraft Airfoil Optimization Using Particle Swarm Optimization Method Applying a Direct Airfoil Design Approach to Obtain the Maximum Lift-to-Drag Ratio

The paper focuses on optimizing the airfoil shape for the Cessna 172 R G1000 training aircraft in order to get the best lift-to-drag ratio without increasing the applied wing current aerodynamics moment. In order to achieve good aerodynamic performance, a swarm-based approach with shape parametrization is used. Particle swarm optimization is used to examine the optimal solution through evolution, whereas XFOIL is used as the main flow field solver. Airfoils are generated continuously using B-splines airfoil parametrization based on the criteria of the particle swarm optimization algorithm until the desired target has been achieved. After the algorithm has attained the desired goal, more shape smoothening is required, which is accomplished using XFOIL. Finally, ANSYS Fluent and a k –ε solver are used to test the airfoil. The major emphasis of the flow simulation is to see if there is flow separation at higher angles of attack and to see if XFOIL results in a more robust solver. Even in a very limited space, the data show a 15% increase in lift-to-drag ratio in cruise settings.