Experiment and computation multi-fidelity multi-objective airfoil design optimization of fixed-wing UAV.

Optimization with a surrogate model is a popular method used in design to avoid a high computational cost problem and is often encountered in computational fluid dynamics and experimental design. However, the optimization with a surrogate model is assigned to solve single-fidelity optimization problems. Thus, a multi-fidelity surrogate model is proposed to solve the multi-fidelity airfoil design problem by combining the data of the wind tunnel experiment and the aerodynamic evaluation using JavaFoil software. In the optimization method, an RBF/Kriging hybrid multi-fidelity surrogate model is used. A non-dominated sorting genetic algorithm II (NSGA-II) is selected to solve the airfoil design problem. The objective of the optimization problem is to minimize the aerodynamic drag and maximize the lift force. The results showed that the algorithm successfully found the UAV airfoil shape and the selected optimum airfoil shape had the error of the aerodynamic lift and drag less than 10 % when tested in the wind tunnel experiment. [ABSTRACT FROM AUTHOR]