Materials Projects
Explore guided student projects in Materials. Build hands-on skills with real aerospace tools and data.
3 projects
Combine with other filters →Test and Compare Material Strength with a Simple ML Model
Break things on purpose, then teach a computer to predict the results
Build and break popsicle-stick or balsa-wood structures, record their dimensions and failure forces, then train a scikit-learn linear regression model to predict strength from geometry. A hands-on bridge between physical testing and machine learning.
Start Project → Some AI/MLPredict Composite Laminate Failure with scikit-learn
Teach a model to predict how and where a composite will fail
Generate a dataset of composite laminate configurations using classical laminate theory, then train a multi-class classifier to predict failure mode — delamination, fiber breakage, or matrix cracking — from layup parameters. Bridges textbook composites theory with practical ML.
Start Project → AI/MLGraph Neural Network for Microstructure-Property Prediction
Turn microscope images into graphs and predict how strong the metal is
Represent alloy or composite microstructure images as graphs — with grains as nodes and boundaries as edges — and train a graph neural network to predict mechanical properties like yield strength and fatigue life. A research-grade application of geometric deep learning to materials science.
Start Project →