Creating Machine-Learning-Friendly Training Data from Crash Simulation Data

A method is presented for generating training data from FEM meshes based on element prop-erties. Learning at the element level is often indicated when larger structures, especially parts, are too inhomogeneous in size or geometry. At the element level, quality metrics and other infor-mation are gathered from the neighborhoods of elements, just as convolutional neural networks for image processing gather information from the neighborhoods of pixels. But in general, neigh-borhoods of elements are not as well structured as pixels in images. Instead, they form irregular graphs which cannot be processed by standard Neural Network (NN) architectures directly.