Aeroelasticity Projects
Explore guided student projects in Aeroelasticity. Build hands-on skills with real aerospace tools and data.
4 projects
Combine with other filters →Physics-Informed Neural Net for Aeroelasticity
Train a neural network that respects the laws of physics
Build a physics-informed neural network (PINN) using DeepXDE to solve aeroelastic flutter equations. Combine deep learning with structural dynamics to predict wing flutter boundaries.
Start Project → Some AI/MLBuild a Flutter Demo and Predict Vibration Frequency
Feel aeroelasticity with a homemade wing in front of a fan
Build a simple cantilever wing from cardboard or balsa, measure vibration frequency at different wind speeds using a phone accelerometer, then fit a regression model to predict frequency from speed.
Start Project → AI/MLPredict Wing Flutter Speed with Gradient Boosting
Train XGBoost to replace hours of aeroelastic simulation
Build a dataset of wing configurations with flutter speeds from analytical or simulation results. Train a gradient-boosted model to predict flutter onset — creating an ML surrogate for computationally expensive aeroelastic analysis.
Start Project → AI/MLML-Based Gust Load Prediction for Wing Structures
Replace expensive time-domain simulations with a trained sequence model
Train a sequence model (LSTM or Transformer) on time-series gust encounter data to predict peak wing root bending moment. Compare against classical 1-minus-cosine gust analysis for a real-world loads problem.
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