FDPI-DeepONet: A novel integration for 3D airfoil flow field computation

Puntos clave

• The integration of FDPI-DeepONet improves accuracy in 3D airfoil flow field computation, allowing better simulation of fluid dynamics.
• The model was evaluated against traditional algorithms, yielding 20% higher predictive accuracy in key flow parameters.
• Assessment included deep learning techniques to analyze and replicate flow patterns with increased precision.
• Implications highlight the potential of deep learning methods in advancing computational fluid dynamics applications.