Aerodynamic design optimization for a canopy based on response surface methodology and a multi-objective genetic algorithm

In the present study, the aerodynamic performance and flight stability of a two-dimensional (2D) canopy in a paraglider are optimized using a combination of response surface methodology (RSM) and a multi-objective genetic algorithm (MOGA) coupled with the unsteady Reynolds-averaged Navier-Stokes (URANS) equations solver. Compared to a 2D base case, an optimized canopy, featured by reduced airfoil thickness, shows an increase in the aerodynamic performance up to 18.9 % based on lift-to-drag ratio, while the flight stability is similar between them. An optimized three-dimensional (3D) canopy is constructed by duplicating the 2D canopy along the arc direction to identify the effects of the optimization on an actual 3D canopy. Based on large-eddy simulation (LES) data of the optimized 3D canopy and base 3D canopy, we show an improvement of the aerodynamic performance and stability of the optimized 3D canopy, consistent with our results from the 2D canopies.