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Physics-Informed Neural Networks for Depth-Averaged Granular Avalanche Dynamics on Curved Topography
Physics-informed neural networks (PINNs) provide a mesh-free framework for solving governing equations, but their application to granular avalanche dynamics over curved terrain remains largely unexplored. This study extends a depth-averaged PINN formulation based on the Savage-Hutter equations to an
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