87 citations · 94 across the 2 of their papers we have counts for
2 papers
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…
cs.CE2018★ 7 cited
Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications
A. Hunter, B. A. Moore, M. K. Mudunuru +9
In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared. Four of the five methods…