ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Airfoil icing and aerodynamic characteristics prediction based on multi-task learning
Received date: 2025-10-28
Revised date: 2025-11-17
Accepted date: 2025-12-15
Online published: 2025-12-29
Supported by
Open Fund of Key Laboratory of Icing and Anti/De-icing(IADL20230302);National Natural Science Foundation of China(12572270);The “1-0” Major Engineering Science Problem Project of Northwestern Polytechnical University(G2024KY0613)
To address the problem of limited accuracy in single-task learning for airfoil icing prediction and the difficulty in simultane-ously obtaining icing morphology and aerodynamic characteristics， a multi-task learning based airfoil icing prediction framework called MTAF （Multi-Task Airfoil Former） is proposed. The framework employs an encoder-decoder architecture that extracts deep representations of airfoil geometry and flight conditions through a shared feature encoder， realizes feature fusion and task interaction via a task correlation module， and accomplishes icing prediction and aerodynamic coefficient prediction respectively through dedicated prediction heads. The performance of Transformer and ConvNeXt backbone net-works within this framework is comparatively studied. Based on training and testing with 625 NACA 2412 airfoil samples， results demonstrate that the Transformer architecture achieves pixel accuracy of 99.79% and coefficient of determination for 0.990 6 in icing prediction tasks， significantly outperforming 99.50% and 0.977 2 of ConvNeXt. For aerodynamic coefficient prediction， Transformer achieves coefficient of determination values of 0.975 4 for lift coefficient and 0.987 4 for drag coefficient， which are comparable to 0.973 3 and 0.990 1 of ConvNeXt， respectively， with each architecture showing distinct advantages. The MTAF framework maintains stable prediction performance across different icing types and various flight conditions， providing a high-precision prediction tool for airfoil icing engineering applications.
Huizhu XIN , Chen LI , Weimin SANG , Liang HOU . Airfoil icing and aerodynamic characteristics prediction based on multi-task learning[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2026 , 47(16) : 132983 -132983 . DOI: 10.7527/S1000-6893.2025.32983
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