feilian-3d: deep-learning prediction of 3D wind fields in cities
Simulation
Deep learning model code predicting 3D wind speed fields in cities from building geometry.
- Resource
- Software & tools
- Method
- ML / surrogate
- Geometry
- City scale
- Topic
- Wind loads & pedestrian wind
- Quantities
- Velocity
- Data volume
- 0 MB
- Year
- 2026
- Licence
- CC BY 4.0
- Creators
- Green, Samuel; Deeptimahanti, Deva; Leong, Iao Hoi; Mann, Tristyn; Abdurakhmanov, Ilkhom; Lu, Jiachen; Nazarian, Negin
- Institution
- Pawsey Supercomputing Research Centre; UNSW; UNSW Sydney
From Zenodo, added 2026-11-07. Listed there as “feilian-3d”. Tags proposed by AI and not yet checked by hand. Spotted a mistake? Tell the portal contacts.