2 papers
physics.ao-ph2025
A Hierarchical Deep Learning Model for Predicting Pedestrian-Level Urban Winds
Reda Snaiki, Jiachen Lu, Shaopeng Li +1
Deep learning-based surrogate models offer a computationally efficient alternative to high-fidelity computational fluid dynamics (CFD) simulations for predicting urban wind flow. H…
physics.ao-ph2024
Advancing Spatio-temporal Storm Surge Prediction with Hierarchical Deep Neural Networks
Saeed Saviz Naeini, Reda Snaiki, Teng Wu
Coastal regions in North America face major threats from storm surges caused by hurricanes and nor'easters. Traditional numerical models, while accurate, are computationally expens…