AI-Powered Airfoil Design Suite

An interactive tool that uses a Deep Learning surrogate model to predict aerodynamic performance and perform inverse design optimization.

Features

• Instant Inference: Predicts $C_L$ and $C_D$ using a trained neural network.
• Inverse Optimization: Automatically suggests NACA parameters ($m, p, t$) to meet a user-defined Target $C_L$.
• Validation: Integrates with XFOIL via AeroSandbox to visualize real-world geometry and performance polars.

Requirements

• Python 3.x
• XFOIL (You must download this separately)

Setup

1. Install dependencies: pip install -r requirements.txt
2. Update the XFOIL_PATH variable in Airfoil_Design_App.py to point to your xfoil.exe.
3. Run the application: python Airfoil_Design_App.py

Simulation

mp4.mp4