# Data repository

## Content

This data publication presents high-resolution measurements of tire contact patch pressure distributions obtained using a capacitive pressure-mapping sensor with 1.6 mm spatial resolution and 65,536 sensing points. 
The dataset captures contact pressures between 69 kPa and 2070 kPa for two commercial truck tires. 
Footprints were recorded at various wheel loads under a constant inflation pressures, providing detailed insight into load-dependent pressure behavior. 
All measurements were taken with the sensor mounted on a flat surface within the experimental setup, while the ika’s tire stiffness test rig ([SteiReP](https://www.ika.rwth-aachen.de/de/kompetenzen/ausstattung/pruefstaende/steirep-de.html)) supplied controlled loading conditions to ensure repeatable data acquisition.

The output of testing machine is stored in Hierarchical Data Format ([HDF5](https://www.hdfgroup.org/solutions/hdf5)). 
[HDF5](https://www.hdfgroup.org/solutions/hdf5/) files can be accessed by software tools like [HDFView](https://www.hdfgroup.org/download-hdfview) or coding languages, e.g. Python using package [`h5py`](https://docs.h5py.org/en/stable/index.html).

### file ``Pirelli_ST_01T_385_55_R22_5_160K.zip``

compressed test results of tire footprint measurements using tire Pirelli ST:01T 385/55 R22.5 160K

### file ``Pirelli_TR_01T_315_70_R22_5_154L.zip`` 

compressed test results of tire footprint measurements using tire Pirelli TR:01T 315/70 R22.5 154L

## References

The data generation as well as the underlying methods, models and software are described in the following publications 

Falla, G.; Yordanov, V.; Leischner, S.; Zeißler, A.: Fourier-finite element analysis of pavements incorporating high precision tire footprint measurements, in: Advances in Materials and Pavement Performance Prediction IV, 2025, 325–328. [DOI:10.34726/9259](https://doi.org/10.34726/9259)

May, M.; Platen, J.; Wollny, I.; Kaliske, M.; Zhao, J.; Liebscher, M.; Mechtcherine, V.; Yordanov, V.; Eckstein, L.; Kupfernagel, B.: The microlayer model: using numerical analyses to uncover the potential of a continuously carbon reinforced concrete pavement, in: Advances in Materials and Pavement Performance Prediction IV, 2025, 71–74. [DOI:10.34726/9259](https://doi.org/10.34726/9259)