Ktirio Cases Dataset

Multiple European city cases for the Urban Building (KUB) application. Each city is provided as a ZIP bundle containing all the data needed to run a KUB simulation end-to-end (GIS, mesh, weather, FMU building models, metadata, and configuration files).

Note: The FMU files and associated metadata (description files) are downloaded or referenced automatically via Feel++ Remote-Data URIs when you run a simulation. You do not need to manually fetch or unpack FMUs—the containerized KUB workflow takes care of it.

Overview

• Dataset name: ktirio-cases
• Number of city cases: 9
• Purpose: Provide ready-to-use input bundles for urban-scale building energy and comfort simulations with Ktirio Urban Building (KUB).
• CKAN landing page:
  https://ckan.hidalgo2.eu/dataset/ktirio-cases

Each ZIP archive includes:

1. GIS metadata
   A JSON (or shapefile) mapping each building’s polygon to its OpenStreetMap (OSM) ID and other attributes.

2. LoD-0 mesh
   An MSH file (mesh_0_Lod0.msh or similarly named) representing the terrain and building footprints at Level-of-Detail 0.

3. Weather CSV
   A time-series file (e.g. weather.csv or weatherPoznan.csv) containing hourly (or sub-hourly) meteorological data. Typical columns include:
   time, temperature_2m, surface_pressure, relative_humidity_2m, wind_speed_10m, wind_direction_10m, direct_radiation, diffuse_radiation, cloud_cover, …

4. FMU building models & descriptions

5. A set of LoD-0 FMU files (e.g. Building_001.fmu, Building_002.fmu, …), each representing a single building’s thermal model.

6. Corresponding metadata description files (XML or JSON) listing the outputs, variable names, and building element IDs.

7. Configuration files

8. A “simulator” config (e.g. idealHeater.cfg or BoilerHeaters.cfg) that lists the FMU URIs (remote or local) and FMU metadata URIs.
9. A “city” config (e.g. strasbourg.cfg, poznan.cfg) that points to the mesh, GIS JSON, and weather CSV, and defines simulation parameters (cem.instance.*, postprocess.*, etc.).

City Bundles Included

• athens.zip – Athens, Greece
• erlangen.zip – Erlangen, Germany
• gyor.zip – Győr, Hungary
• luxembourg.zip – Luxembourg, Luxembourg
• madrid.zip – Madrid, Spain
• nicosia.zip – Nicosia, Cyprus
• poznan.zip – Poznań, Poland
• strasbourg.zip – Strasbourg, France
• stuttgart.zip – Stuttgart, Germany

When you unzip a city bundle (for example, nicosia.zip), you will see a directory structure similar to:

nicosia_input/ ├─ gis.json ├─ mesh_lod0.msh ├─ weather.csv ├─ nicosia.cfg ├─ idealHeater.cfg # or BoilerHeaters.cfg

Tip: Since FMUs and metadata can be large, the .cfg files often reference them via remote-data URIs (e.g. girder:{file:,api_key:${api_key_girder}}). KUB will download and cache them automatically at runtime.

How to Use a City Bundle

Below is a minimal workflow for running a KUB simulation on, for example, the Kernante dataset. The same steps apply to any other city case:

1. Download & Unzip

```bash

Download the city ZIP from CKAN

wget https://ckan.hidalgo2.eu/dataset/ktirio-cases/resource/{city}.zip -O {city}.zip

Unzip the archive into a folder named "{city}_input"

unzip {city}.zip -d {city}_input ```

Replace {city} with one of: athens, erlangen, gyor, luxembourg, madrid, nicosia, poznan, strasbourg, stuttgart

2. Create an Output Directory

bash mkdir kub_outputs

3. Pull the KUB Container

bash apptainer pull -F kub.sif oras://ghcr.io/feelpp/ktirio-urban-building:master-sif

• This command downloads kub.sif (the Apptainer image).
• You can also use Singularity if it is installed on your system.

4. Run the Simulation

Set the Apptainer home directory so that all outputs are written into your local kub_outputs folder:

bash export APPTAINER_HOME=$PWD/kub_outputs

Then run using MPI (example with 4 processes):

bash mpiexec -n 4 --bind-to core apptainer exec -B ./{city}_input/:/input_data/ --env OMP_NUM_THREADS=1 kub.sif feelpp_kub_cem --config-files /input_data/idealHeater.cfg /input_data/{city}.cfg

• The --config-files argument points first to the “simulator” config (idealHeater.cfg) and then to the “city” config ({city}.cfg).
• Adjust {city} (e.g. strasbourg) and directory names accordingly.

Note (Gaya cluster):
If running on Gaya, add --bind /opt/:/opt/ so that Dymola’s libraries are available inside the container.

5. Inspect Results

After the simulation completes, you will find output files under:

kub_outputs/feelppdb/{city}_output/instances/np_4/lod0/exports/City_Energy_Modeling.case

• Open City_Energy_Modeling.case in ParaView (desktop) or via the Ktirio WASM/GUI.
• CSV/HDF5 exports and generated reports appear in the same folder.

Simulation Reports & Dashboard

All nine city cases have been executed and aggregated into a shared reporting portal:

Interactive Dashboard: https://cases.ktirio.fr

From the dashboard you can: - Browse precomputed 3D visualizations (e.g., exterior/interior temperature, solar masks).
- View time-series plots of building energy demands (heating, cooling).
- Drill down into building-level vs. city-level benchmarking tables.
- Download raw CSV/HDF5 data or EnsightCase Gold files without rerunning simulations.

Licensing & Provenance

• Each city archive on CKAN is marked as “License not specified.” In practice, the data bundles were prepared by the HiDALGO2 consortium (Feel++ / Unistra).
• FMU files were generated using open-source Modelica libraries from the Feel++ ecosystem.
• Some building submodels may include proprietary components; check individual FMU license notices if you plan to redistribute or modify them.

Summary

• The ktirio-cases dataset on CKAN provides nine European city input bundles for KUB.
• Each bundle contains GIS, mesh, weather, FMUs, metadata, and configuration files so you can run a city-scale building-energy simulation out of the box.
• FMU and metadata downloads are handled automatically at runtime by KUB via Feel++ Remote-Data URIs.
• To explore results without rerunning, visit https://cases.ktirio.fr for interactive reports, visualizations, and ready-to-download outputs.