Thermodynamically Consistent Machine Learning for Fracture Prediction in Heterogeneous Materials
The results show that the proposed Thermodynamically Consistent Latent Dynamics Identification for parametric systems can more accurately capture both fracture patterns and the subsequent fracture evolution than the purely data-driven Autoencoder Long Short-Term Memory (AE-LSTM) model.
Muhamad Alim, Xiao-Long He, Mei-Na Tsao et al.
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