3 papers
cs.LG2025
WindMiL: Equivariant Graph Learning for Wind Loading Prediction
Themistoklis Vargiemezis, Charilaos Kanatsoulis, Catherine Gorlé
Accurate prediction of wind loading on buildings is crucial for structural safety and sustainable design, yet conventional approaches such as wind tunnel testing and large-eddy sim…
physics.comp-ph2025
From large-eddy simulations to deep learning: A U-net model for fast urban canopy flow predictions
Themistoklis Vargiemezis, Catherine Gorlé
Accurate prediction of wind flow fields in urban canopies is crucial for ensuring pedestrian comfort, safety, and sustainable urban design. Traditional methods using wind tunnels a…
physics.flu-dyn2025
Developing a Numerical Framework for the High-Fidelity Simulation of Contrails: Sensitivity Analysis for Conventional Contrails
Tânia S. C. Ferreira, Juan J. Alonso, Catherine Gorlé
Contrails have recently gained widespread attention due to their large and uncertain estimates of effective radiative forcing, i.e., warming effect on the planet, comparable to tho…