3 papers
cs.LG2026
Toward AI-Driven Digital Twins for Metropolitan Floods: A Conditional Latent Dynamics Network Surrogate of the Shallow Water Equations
Phillip Si, Yuan Qiu, Omar Sallam +4
AI-driven flood digital twins demand fast hydrodynamic surrogates for ensemble forecasting and observation assimilation. Yet even GPU-accelerated two-dimensional shallow water equa…
physics.flu-dyn2026
Conditional diffusion denoising probabilistic model for super-resolution of atmospheric boundary layer large eddy simulation
Omar Sallam, Mirjam Fürth
Climate change necessitates rapid expansion of renewable energy, with wind energy offering a scalable and low-impact solution. However, accurate prediction of wind loads and power…
physics.flu-dyn2024
Inference of water waves surface elevation from horizontal velocity components using physics informed neural networks (PINN)
Omar Sallam, Mirjam Fürth
In this paper, a mathematical model is presented to infer the wave free surface elevation from the horizontal velocity components using Physics Informed Neural Network (PINN). PINN…