most citedLearning to fail: Predicting fracture evolution in brittle material models using recurrent graph convolutional neural networks

87 citations · 87 across the 1 of their papers we have counts for

collaborators

1 paper

cond-mat.mtrl-sci2018★ 87 cited

Learning to fail: Predicting fracture evolution in brittle material models using recurrent graph convolutional neural networks

Max Schwarzer, Bryce Rogan, Yadong Ruan +8

We propose a machine learning approach to address a key challenge in materials science: predicting how fractures propagate in brittle materials under stress, and how these material…