2026-10-14T18:50:46Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33743488 2026-09-14T16:27:13Z category_25888 item_type_3 month_year_09_2026

Data and code for Scheduled Momentum Diffusion Improves Hydraulic Shock Fidelity in Strong-Form Shallow-Water Physics-Informed Neural Networks Huicong An (24888058) Chaojun Ouyang (17321725) Surface water hydrology Physics-informed neural network; Shallow Water Equations hydraulic shock Dam-break flows <pre>Companion data and code for "Scheduled Momentum Diffusion Improves Hydraulic Shock Fidelity in Strong-Form Shallow-Water Physics-Informed Neural Networks" by Huicong An and Chaojun Ouyang.<br><br>The package includes 102 formal shallow-water PINN experiments covering nine dam-break depth ratios (2:1 to 10:1), diffusion ablations, bounded Fourier/RAR/weak-form comparisons, a strong learned bed step, radial two-dimensional flow, a matched conservative-residual comparison, alternative diffusion operators, and steady subcritical flow over a smooth bump. Formal comparisons retain all three seeds (2025, 2026 and 2027).<br><br>Contents comprise source code, resolved physical/training configurations, prediction fields, per-seed metrics, analytical references, three radial FVM reference grids, four Xia2017 smooth-step cross-checks, figure/table source data, and executable reproduction commands. The model archive contains 102 final states and 48 additional states supporting the training-evolution analysis. Configuration and evaluation records for 36 auxiliary calibration/selection runs are retained without their full fields or model weights.<br><br>The code_and_data archive supports rebuilding all six main and six supplementary figures, generating numerical summaries for all six tables, and recomputing field/reference metrics without retraining. The trained_models archive additionally supports inference checks and hydraulic re-evaluation. PINN and FVM environments are documented separately. Software is licensed under MIT; numerical data, model weights, figures and standalone documentation are licensed under CC BY 4.0. See README.md and the file-level license map for details.</pre><p></p> 2026-09-14T16:27:13Z Dataset Dataset 10.6084/m9.figshare.33743488.v2 https://figshare.com/articles/dataset/Data_and_code_for_Scheduled_Momentum_Diffusion_Improves_Hydraulic_Shock_Fidelity_in_Strong-Form_Shallow-Water_Physics-Informed_Neural_Networks/33743488 MIT