Co-Kriging Based Multi-Fidelity Aerodynamic Optimization for Flying Wing UAV with Multi-Shape Wingtip Design

Abstract

Wingtip aerodynamic optimization is an important supplementary to improve the aerodynamic performance of flying wing UAVs. Based on the Co-Kriging model, this paper studies the optimal design of wingtips and the influence of different wingtip shapes on the aerodynamic performance of the whole aircraft. Firstly, we formulate the problem as minimizing the drag coefficient under given conditions, with the optimization variables are the sweep angle, the taper ratio, the dihedral angle and the twist angle of the wingtip. Then, a joint high-fidelity and low-fidelity Co-Kriging model is applied to reduce the computational cost of the aerodynamic optimization. Explicitly, the high-fidelity analysis adopts the Reynolds average Navier Stokes (RANS) method, while the low-fidelity analysis adopts the three-dimensional (3-D) panel method. Next, based on the proposed Co-Kriging model, we introduce the Genetic Algorithm (GA) to optimize the aerodynamic performance. Simulation results show that, compared with the baseline design, the drag coefficient can be reduced by up to 8.77 counts with the addition of the wingtip optimization, which brings aerodynamic performance gains for the flying wing UAV.