Abstract
The present work investigates the effect of both surface roughness and particle morphology on the retention behaviour of granular materials via X-ray micro-computed tomography (µCT) observations. X-ray µCT images were taken on two types of spherical glass beads (i.e. smooth and rough) and two different sands (i.e. natural and roughened). Each sample was subjected to drainage and soaking paths consisting in a multiphase ‘static’ flow of potassium iodine (KI) brine (wetting phase) and dry air (non-wetting phase). Tomograms were obtained at different saturation states ranging from fully brine saturated to air dry conditions with 6.2 μm voxel size resolution. The data acquisition and pre-processing are here described while all data, a total of 48 tomograms, are made publicly available. The combined dataset offers new opportunities to study the influence of surface roughness and particle morphology on capillary actions as well as supporting validation of pore-scale models of multiphase flow in granular materials.
Original language | English |
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Article number | 78 |
Number of pages | 7 |
Journal | Scientific data |
Volume | 11 |
Issue number | 1 |
DOIs | |
Publication status | Published - 16 Jan 2024 |
Bibliographical note
Publisher Copyright:© 2024, The Author(s).
Funding
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101005611 for Transnational Access conducted at Ghent University. Furthermore, we are grateful for the Ghent University Special Research Fund (BOF-UGent) to support the Centre of Expertise UGCT (BOF.COR.2022.0009), and the Research Foundation - Flanders (FWO; G051418N)”. The roughness measurements and initial SEM observations were funded by EPSRC grant number EP/001766/1 as a part of ‘Friction: The Tribology Enigma’ Programme Grant. Sharon Ellman is a PhD Fellow with the Research Foundation – Flanders (FWO) and acknowledges its support under grant 1182822 N. S. Manoorkar also acknowledges the support of the FWO under grant G004820N.
Funders | Funder number |
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BOF-UGent | |
Centre of Expertise UGCT | BOF.COR.2022.0009 |
Ghent University Special Research Fund | |
Horizon 2020 Framework Programme | 101005611 |
Engineering and Physical Sciences Research Council | EP/001766/1 |
Fonds Wetenschappelijk Onderzoek | G051418N, 1182822, G004820N |