Wings in a Minute: How AI Became an Aerodynamic Genius ⚡ экспресс
Scientists have created a neural network that, having studied thousands of wing shapes, quickly learns to predict the airflow over new ones. It's like an experienced driver who, having mastered many cars, easily gets used to an unfamiliar model. Now engineers can improve aerodynamics faster. What if we trained robots the same way to work in zero gravity?
Training an accurate aerodynamic model is like culinary art: first, a chef masters hundreds of recipes to grasp the general principles, then easily perfects a specific dish. Engineers created AeroTransformer and fed it 30,000 different wing shapes — a whole galaxy of culinary ideas galaxy. In calculations, air behaves like water in a pot water: smoothly flowing around surfaces, simplifying computer prediction.
After fine-tuning on just 450 samples, error dropped to 0.36% — six times more accurate than starting from scratch. The approach sharply reduces entropy entropy (uncertainty) in predictions.
An online tool already lets you change wing shape in a browser and see the result instantly. The developers have open-sourced the code and data — now any researcher can fine-tune the model for turbines or racing cars.
🎯 The model is already working on the WebWing website: move the wing with your mouse and watch lift in real time.