Data-guided finite-volume PINNs for 2D shallow water equations avoid trivial low-momentum collapse via sparse measurements, achieving up to 22x error reduction on benchmarks and accurate surrogates on real river data.
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Finite Volume-Informed Neural Network Framework for 2D Shallow Water Equations: Rugged Loss Landscapes and the Importance of Data Guidance
Data-guided finite-volume PINNs for 2D shallow water equations avoid trivial low-momentum collapse via sparse measurements, achieving up to 22x error reduction on benchmarks and accurate surrogates on real river data.