New AI tool calculates materials’ stress and strain based on photos
MIT researchers developed a machine-learning technique to determine properties of a material based on an image of the material’s internal structure.
The researchers turned to a machine learning technique called a Generative Adversarial Neural Network. They trained the network with thousands of paired images — one depicting a material’s internal microstructure subject to mechanical forces, and the other depicting that same material’s color-coded stress and strain values. With these examples, the network uses principles of game theory to iteratively figure out the relationships between the geometry of a material and its resulting stresses.
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