Visual characterization of displacement processes in porous media

DOI

This dataset correlates to the submitted article to IEEE VIS 2023, entitled “Visual Analysis of Displacement Processes in Porous Media using Spatio-Temporal Flow Graphs”, by Straub et al. 2023. More specifically, this data set is the one used to create the graphs shown in all Figures, except Figure 2, of the article. In this work, 11 experiments were carried out in a Poly-Di-Methyl-Siloxane (PDMS) micromodel for a variety of capillary numbers and viscosity ratios between the phases involved. More specifically, the used viscosity ratios between the wetting and the non-wetting phase were 0.2, 1, 10. The corresponding capillary numbers (on log scale) were -2, -3, -4, -5. Two additional experiments carried out in two micromodels having the same distribution of grains but different grain shape, and another one with a pore structure based on Delaunay triangulation. The objective of the work was to establish a visualization workflow which can facilitate the extraction of information in a generic way, independently of the boundary flow conditions, or the physical properties of the fluids, and the geometry of the pore space.

The micromodels used, which served as the porous medium, were of four types, as mentioned before. The micromodels were produced by following the standard optical and soft lithography techniques, meaning that a silicon wafer was prepared with the features of each flow network on it, and then the PDMS elastomer base was mixed with the curing agent at a ratio of 1:10, degassed, poured on top of the wafer, degassed, thermally cured, and then bonded with corona treatment. The dimensions of the pore space of two of the models were 4 mm × 6 mm in the planar view, and a depth of 115 μm, constant throughout the entire pore space. The pore network was based on a statistical distribution of points in the pore space. One design had 76 non-overlapping circular grains in planar view (Network 1), with a distribution for the radius, and the other one had as grains the inscribed to the circles octagons (Network 2). The grain diameter in both cases ranged from 275 to 575 μm, with a mean size of 380 μm. The third type of micromodels (Network 3) had a pore network with overall dimensions of 15 mm × 20 mm and a depth of 100 μm. The pore network was again based on a statistical distribution of points in the pore space, with 85 cylindrical grains with a mean pore size of 420 μm, and a mean grain diameter of 1.63 mm. Finally, the last network (Network 4) was based on 5000 points generated by Delaunay triangulation, and their connections. The total dimensions of the network were 5 mm x 30 mm, but we could visualize an area of 5 mm x 6 mm, and this is what we account for as the domain size. The mean pore size was 50 μm, as well as the depth of the flow network.

The microfluidic chips were not treated in any way to tune or alter their surface electrostatic properties, and in their natural state they are hydrophobic. They were treated as such in the experiments too, with the two fluid phases involved being water dyed with a water-based ink, to create the contrast for visual evaluation of the flow, as the non-wetting phase, and Fluorinert FC-43, which served as the wetting phase. For the tuning of the viscosity of the non-wetting phase, 99.5% glycerol was used to achieve the desired viscosity. The addition of the ink in water, and of glycerol when applicable, did not alter its physical properties, meaning that the density and the viscosity of the final mixture was practically the same as those of pure water at the same temperature (20 degrees Celsius).

During each experiment there was a fixed value for the volumetric flux of the non-wetting phase, corresponding to a fixed capillary number. The wetting phase was already present in the pore space, so drainage scenarios were realized. The introduction of the non-wetting phase in the pore space was done with one neMESYS mid pressure syringe pump 1000N. The control of the syringe pump was done with QmixElements© and a personal computer. During the displacement events, pictures from the pore space were recorded with the use of StreamPix 8.0©. The acquisition frame rate would vary between 1 and 15 frames per second, depending on the speed of the process.

The data files are the pictures taken during each event, and are structured accordingly based on the pore network, the capillary number, the viscosity ratio, and frames per second.

StreamPix, 8.0

CETONI QMixElements, v20190108

To be published in a special issue of TVCG for the IEEE VIS 2023 conference proceedings.

Identifier
DOI https://doi.org/10.18419/darus-3615
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/darus-3615
Provenance
Creator Karadimitriou, Nikolaos ORCID logo; Lee, Dongwon ORCID logo; Steeb, Holger ORCID logo
Publisher DaRUS
Contributor Karadimitriou, Nikolaos; Steeb, Holger; Institute of Applied Mechanics (MIB) - Chair for Continuum Mechanics; Lee, Dongwon; University of Stuttgart; Institute of Applied Mechanics
Publication Year 2023
Funding Reference DFG EXC 2075 - 390740016 ; DFG 327154368 - SFB 1313
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Karadimitriou, Nikolaos (University of Stuttgart); Steeb, Holger (University of Stuttgart & SC SimTech)
Representation
Resource Type Experimental; Dataset
Format application/x-tar
Size 1167174144; 4607971840; 6390583808; 446751232
Version 1.0
Discipline Construction Engineering and Architecture; Earth and Environmental Science; Engineering; Engineering Sciences; Environmental Research; Geosciences; Natural Sciences; Physics
Spatial Coverage University of Stuttgart, Institute of Applied Mechanics (CE), Stuttgart, 70569, Germany