4 papers · 1 filter
Learned Response-Field Inertia Operator for HEC-RAS 2D Water-Surface Elevation Prediction
Edward Holmberg, Elias Ioup, Md Meftahul Ferdaus +2
This article presents a cross-dataset evaluation of learned native-cell surrogate models for solver-consistent water-surface elevation (WSE) prediction in HEC-RAS 2D. To avoid rast…
Accelerating HEC-RAS: A Recurrent Neural Operator for Rapid River Forecasting
Edward Holmberg, Pujan Pokhrel, Maximilian Zoch +9
Physics-based solvers like HEC-RAS provide high-fidelity river forecasts but are too computationally intensive for on-the-fly decision-making during flood events. The central chall…
Physics-Informed Neural Network Surrogate Models for River Stage Prediction
Maximilian Zoch, Edward Holmberg, Pujan Pokhrel +8
This work investigates the feasibility of using Physics-Informed Neural Networks (PINNs) as surrogate models for river stage prediction, aiming to reduce computational cost while m…
STROOBnet Optimization via GPU-Accelerated Proximal Recurrence Strategies
Ted Edward Holmberg, Mahdi Abdelguerfi, Elias Ioup
Spatiotemporal networks' observational capabilities are crucial for accurate data gathering and informed decisions across multiple sectors. This study focuses on the Spatiotemporal…