Effect of Far-field Boundary on PINN Solutions for NACA0012 Airfoil at Moderate Reynolds Number
Abstract
Physics-Informed Neural Networks (PINNs) have recently gained considerable attention owing to their ability to solve fluid flows in a meshless fashion using feed-forward deep neural networks, while adhering to the physical laws governing fluid flow. However, their applications are currently limited to low Reynolds number (
Fields of Study & Subjects
Model Reduction and Neural Networks
Computational Fluid Dynamics and Aerodynamics
Neural Networks and Applications
Publication details
- Journal / source
- AIAA SciTech Forum
- Publication date
- 8 January 2026