All projects
Physics-Grounded AI Surrogate for Bridge Scour and Digital-Twin Decisions
Highlights
- CFD and flume experiments build the DBscour database
- Bayesian DeepONet predicts full-field scour in seconds
- Reliability analysis links scour risk to bridge safety grades A–E
- Digital-twin alerts with time-to-critical for pre-emptive action
Related publications
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Interpretable machine learning scheme for predicting bridge pier scour depth
Computers and Geotechnics 170 · 2024
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Transportation Geotechnics 52 · 2025
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Probabilistic prediction of local scour at bridge piers with interpretable machine learning
Water 17(24) · 2025
- Funded by
- MOLIT Young Researcher Program (KAIA)
- Period
- 2026–2028
- Status
- Ongoing
- Area
- Infrastructure AI