南京航空航天大学学报（英文版）2025，Vol.42Issue(1)：56-69,14.DOI:10.16356/j.1005-1120.2025.01.004
基于两步深度学习逆向设计方法考虑非地面效应的高速地效翼型优化
Optimization of High-Speed WIG Airfoil with Consideration of Non-ground Effect by a Two-Step Deep Learning Inverse Design Method
摘要
Abstract
Under complex flight conditions,such as obstacle avoidance and extreme sea state,wing-in-ground(WIG)effect aircraft need to ascend to higher altitudes,resulting in the disappearance of the ground effect.A design of high-speed WIG airfoil considering non-ground effect is carried out by a novel two-step inverse airfoil design method that combines conditional generative adversarial network(CGAN)and artificial neural network(ANN).The CGAN model is employed to generate a variety of airfoil designs that satisfy the desired lift-drag ratios in both ground effect and non-ground effect conditions.Subsequently,the ANN model is utilized to forecast aerodynamic parameters of the generated airfoils.The results indicate that the CGAN model contributes to a high accuracy rate for airfoil design and enables the creation of novel airfoil designs.Furthermore,it demonstrates high accuracy in predicting aerodynamic parameters of these airfoils due to the ANN model.This method eliminates the necessity for numerical simulations and experimental testing through the design procedure,showcasing notable efficiency.The analysis of airfoils generated by the CGAN model shows that airfoils exhibiting high lift-drag ratios under both flight conditions typically have cambers of among[0.08c,0.105c],with the positions of maximum camber occurring among[0.35c,0.5c]of the chord length,and the leading-edge radiuses of these airfoils primarily cluster among[0.008c,0.025c].关键词
条件生成对抗网络/人工神经网络/翼型设计/地效翼飞行器/地面效应Key words
conditional generative adversarial network(CGAN)/artificial neural network(ANN)/airfoil design/wing-in-ground(WIG)aircraft/ground effect引用本文复制引用
王晨鹭,孙建红,郑达仁,孙智,左思,刘浩,李佩..基于两步深度学习逆向设计方法考虑非地面效应的高速地效翼型优化[J].南京航空航天大学学报（英文版）,2025,42(1):56-69,14.基金项目
Acknowledgements This work was supported by the Prior-ity Academic Program Development of Jiangsu Higher Edu-cation Institutions,the Fundamental Research Funds for the Central Universities(No.ILA220101A23),CARDC Funda-mental and Frontier Technology Research Fund(No.PJD20200210),and the Aeronautical Science Foundation of China(No.20200023052002). （No.ILA220101A23）
