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Thermodynamically Consistent Machine Learning for Fracture Prediction in Heterogeneous Materials
Understanding fracture behavior is critical for assessing the structural integrity and longevity. Highly time-consuming physics-based fracture simulations motivate the development of machine-learning-based fracture evolution prediction with surrogate models. However, most existing machine-learning m
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