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pro vyhledávání: '"Pash, Calvin R."'
Here we assess the applicability of graph neural networks (GNNs) for predicting the grain-scale elastic response of polycrystalline metallic alloys. Using GNN surrogate models, grain-averaged stresses during uniaxial elastic tension in Low Solvus Hig
Externí odkaz:
http://arxiv.org/abs/2205.06324
