Where infrared.city fits
3,204,804 simulations run on Infrared Core (as of 29 Oct 2026).
infrared.city runs 12 models from one engine, Infrared Core, among them wind, wind comfort, sun, daylight, radiant heat and felt heat (UTCI). It works on real 3D building and terrain meshes, in a browser app, through an API and SDK, and in plugins for Grasshopper, QGIS and ArcGIS. Felt heat for 1 km² takes about 5 s once the geometry is uploaded, and 400 km² took 44 s as four 100 km² runs in parallel. Run times are not like for like across tools: area, grid, simulated hours and physics differ. Sun, sky and radiant heat come from ray tracing. Wind comes from an AI model trained on CFD results, not from a CFD run for each request.
- You test many massing and street options for a block, a district or a whole city.
- You need felt heat, sun, daylight and wind comfort from one engine.
- You want a Python or TypeScript SDK for your own tools.
- You need an hourly city layer for a digital twin.
Use both
Use infrared.city to compare options quickly. Run a detailed CFD wind study of the chosen design in SimScale when a planning report needs one.
Facts side by side
| infrared.city | SimScale | |
|---|---|---|
| Method | Ray tracing for sun, sky and radiant heat; wind from an AI model trained on CFD results (no CFD run per request) | Lattice Boltzmann Method on GPUs, k-omega SST DDES turbulence model |
| Run time | About 5 s for 1 km² of felt heat (UTCI, 08 to 18 h, geometry uploaded, measured); 400 km² in 44 s (four runs in parallel) | Vendor: solve times "rarely longer than a few hours for a complex case" |
| Inputs | Real 3D building and terrain meshes, weather data; trees and ground materials for heat | Rhino (.3dm) or STL geometry |
| Outputs | 12 models, among them wind, wind comfort, sun, daylight, radiant heat and felt heat (UTCI) | Wind comfort maps with criteria such as Lawson, Davenport and NEN 8100 |
| Runs as | Cloud: browser app, API and SDK, plugins | Browser, cloud |
The run times are not like for like: SimScale computes CFD; infrared.city uses an AI wind model trained on CFD results.
The infrared.city values repeat the full comparison. Each value for SimScale comes from the sources below.
Sources
- SimScale docs: pedestrian wind comfort analysis , accessed 30 Oct 2026.
- SimScale: urban microclimate , accessed 30 Oct 2026.