Benchmark package for source inversion of urban pollution dispersion using building geometry and sparse sensors, including PPMLES/MUST summaries. Useful for testing inversion and sensing methods.
Example CFD simulation and code for distributed training of a U-Net predicting urban aerodynamic flow and pollutant dispersion. Useful for ML surrogates of urban flow.
The Architectural Institute of Japan (AIJ) urban wind environment benchmark suite: wind-tunnel and field data for cases A–M, from a single high-rise building and cube arrays to real districts such as Shinjuku and Niigata, many with STL geometry. Widely used to validate CFD for pedestrian-level wind and dispersion.
From Zenodo, added 2026-11-07.
Listed there as “High-Resolution Dataset of Time-Integrated 3D Urban Pollutant Concentration Fields”. Tags proposed by AI and not yet checked by hand. Spotted a mistake? Tell the portal contacts.