The parameterization of airfoil geometry has a profound influence on optimization results and calculation efficiency. A good parametric method should have a large optimization space, good local control ability, fewer design variables, and at the same time ensure the requirements of geometric shape smoothness in the optimization process. The class and Shape Transformation method proposed by Kulfan has been widely used for its excellent robustness and smooth geometric description ability. This method can ensure that the leading edge radii of the upper and lower airfoil surfaces are equal. In this paper, NACA0012 and RAE2822 airfoil are fitted with different order shape functions. An application was carried out to generate a new airfoil mesh based on an existing mesh and a new airfoil using CST method and dynamic mesh technology.

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The particle swarm optimization algorithm was introduced and the six-hump camelback function problem was verified and tested. The flow field of the RAE2822 airfoil was simulated by the Navier-Stokes equation and compared with the experiment very well. Based on the aerodynamic optimization case of an airfoil, an optimization design and drag reduction design with a lift coefficient fixed were developed. In this problem, geometric constraints and aerodynamic constraints are both involved. A population of 30 individuals was generated. The CST airfoil parameterized method was used to generate the new airfoil, and the dynamic mesh technique was used to update the new mesh. The aerodynamic characteristics of each airfoil was simulated by Navier-Stokes equation and obtain the individual fitness value. A total of 20 iterations of the design were carried out. There was a strong shock wave and a large shock drag in the baseline airfoil transonic flow. The shock strength is obviously weakened after optimization. The pressure drag is obviously reduced, and the lift-drag ratio is increased by 75%.

Particle swarm optimization algorithm has the characteristics of global optimization. The Euler equation with CST airfoil parameterization is used to ensure the generation of smooth airfoil. The airfoil reverse design optimization system is build based on particle swarm optimization algorithm. The design practice shows that the optimization algorithm developed in this paper can greatly improve the efficiency of optimization design and has good practical value in engineering.