Aerodynamic Optimization of a Morphing Leading Edge Airfoil with a Constant Arc Length Parameterization

The paper presents the aerodynamic optimization of a morphing leading edge airfoil using a parameterization based on the class/shape transformation (CST) technique associated with a dedicated procedure to keep the arc length of the curve constant in order to limit the axial stress of the deformed shapes. The optimization is performed with a standard methodology based on genetic algorithms, comparing the results for three different aerodynamic models. Whereas the solutions obtained with the third model are standard droop nose shapes, those found via transitional models show an uncommon deformation with an upward leading edge deflection. A metamodel-assisted optimization loop is used to solve a known problem, showing that an artificial neural network is able to provide a reduction of the convergence effort when approximating the highly nonlinear relationship between the constant arc length parameterization and the aerodynamic behavior predicted with two of the models.