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Physics-informed surrogate of urban wind from sparse measurements

Field 30 MB

Field and CFD data for physics-informed surrogate modelling of urban wind under sparse measurements.

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Licence
CC BY 4.0 Free to use and share, including commercially, as long as you credit the creators.
Size
30 MB

How to cite

Hongyuan, H., & Han, Z. (2026). Physics-Informed Surrogate Modeling of Urban Wind Environments under Sparse Measurements: A Pressure-Free Parameterized PINN with Soft Geometric Constraints [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18789258

Check the repository for the citation its authors prefer.

Details

Resource
Measurements, Simulation output
Method
Field, RANS, ML / surrogate
Geometry
Realistic neighbourhood
Topic
Wind loads & pedestrian wind
Quantities
Velocity
Year
2026
Creators
Hongyuan, Huo; Han, Zhang

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From Zenodo, added 2026-11-07. Listed there as “Physics-Informed Surrogate Modeling of Urban Wind Environments under Sparse Measurements: A Pressure-Free Parameterized PINN with Soft Geometric Constraints”. Tags proposed by AI and not yet checked by hand. Spotted a mistake? Tell the portal contacts.