Data-Based Approach for Fast Airfoil Analysis and Optimization

摘要

Airfoils are of great importance in aerodynamic design, and various tools have been developed to evaluate and optimize their performance. Existing tools are usually either accurate or efficient, but not both. This paper presents a tool that can analyze airfoils in both subsonic and transonic regimes in about one-hundredth of a second, and optimize airfoil shapes in a few seconds. Camber and thickness mode shapes derived from over 1000 existing airfoils are used to parameterize the airfoil shape, which reduces the number of design variables. More than 100,000 Reynolds-averaged Navier-Stokes (RANS) evaluations associated with different airfoils and flow conditions are used to train a surrogate model that combines gradient-enhanced kriging, partial least squares, and mixture of experts. These surrogate models provide fast aerodynamic analysis and gradient computation, which are coupled with a gradient-based optimizer to perform rapid airfoil shape design optimization. When comparing the surrogate-based optimization with optimization based on direct RANS evaluations, the largest differences in minimum C-d are 0.04 counts for subsonic cases and 2.5 counts for transonic cases. This approach opens the door for interactive airfoil analysis and design optimization using any modern computer or mobile device.