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.

使用代理模型进行优化是设计中常用的一种避免高计算成本问题的方法，在计算流体动力学和实验设计中经常遇到。然而，使用代理模型的优化被分配来解决单保真优化问题。为此，结合风洞实验数据和JavaFoil软件气动评估，提出了一种多保真代理模型来解决多保真翼型设计问题。在优化方法中，使用了 RBF/Kriging 混合多保真代理模型。选择非支配排序遗传算法II（NSGA-II）来解决翼型设计问题。优化问题的目标是最小化气动阻力和最大化升力。