SFB 1313 is an interdisciplinary Collaborative Research Centre of the University of Stuttgart, consisting of four major project areas (A-D), divided in 17 individual research projects. It is funded by the German Research Foundation (DFG) and affiliated to the Cluster of Excellence "Data-integrated Simulation Science (SimTech)".

Interfaces have a great impact on multi-field processes (flow, transport and deformation) in porous-media systems. SFB 1313 aims to research these interfaces and to gain a fundamental understanding how they affect multi-field processes. An important step is therefore to quantify how the dynamics of fluid-fluid and fluid-solid interfaces in porous-media systems are affected by pore geometry, heterogeneity and fractures. Furthermore, developing experimental knowledge as well as mathematical and computational models will support SFB 1313‘s research.

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SorptionCoefficientsAndConcentrationsFitted.tar
Jun 16, 2020 - EICP Model Calibration
TAR Archive - 800.1 KB - MD5: 90b379d0b9814d744591028dee73ea79
Simulation
SorptionCoefficientsAndKureaseFitted.tar
Jun 16, 2020 - EICP Model Calibration
TAR Archive - 795.8 KB - MD5: 71e1fc0cda6aecbb6f5c4909911d0aa6
Simulation
SorptionCoefficientsAndPKAFitted.tar
Jun 16, 2020 - EICP Model Calibration
TAR Archive - 796.2 KB - MD5: 3b9a710a47f130f00f948548ff2e7805
Simulation
SorptionCoefficientsOnlyFitted.tar
Jun 16, 2020 - EICP Model Calibration
TAR Archive - 794.3 KB - MD5: 90eda7814a3a2e0f4386ac36686a904f
Simulation
Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC
May 19, 2020 - B04: Hybrid discrete-continuum models for fractured porous media: model choice and random field/network generation
Reuschen, Sebastian; Xu, Teng; Nowak, Wolfgang, 2020, "Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC", https://doi.org/10.18419/DARUS-741, DaRUS, V1
This dataset contains the code and all relevant data and of the paper "Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC" by Sebastian Reuschen, Teng Xu and Wolfgang Nowak. Always cite the paper together with this dataset because this dataset is not self-explanatory. The code.tar.gz file conta...
code.tar.gz
May 19, 2020 - Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC
Gzip Archive - 143.7 KB - MD5: 434750ea8b39b02bc74c456d12660e5c
data.tar.gz
May 19, 2020 - Code and data of Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC
Gzip Archive - 580.8 MB - MD5: 3a5ff7270f32fae9c2890e2c94837ec0
micro-XRCT data set of open-pored asphalt concrete
Mar 12, 2020 - Publication: An open, modular, and flexible micro X-ray computed tomography system for research
Ruf, Matthias; Steeb, Holger, 2020, "micro-XRCT data set of open-pored asphalt concrete", https://doi.org/10.18419/DARUS-639, DaRUS, V1
micro-XRCT data set (projection and reconstructed images) resulting from a region of interest scan (diameter 48.41 mm, height 35.46 mm) located in the center of an open-pored asphalt concrete core with 100 mm diameter and 50 mm length.
projections.rar
Mar 12, 2020 - micro-XRCT data set of open-pored asphalt concrete
RAR Archive - 4.6 GB - MD5: 3e423fc9e93c96efbbcf59e3f7c036bb
Projection images (360 deg, angle increment 0.25 deg), dark image (di) and open beam image (ob) in 16 bit *.tif file format.
reconstructed.rar
Mar 12, 2020 - micro-XRCT data set of open-pored asphalt concrete
RAR Archive - 6.6 GB - MD5: 76dc464f2c8d087d092fc6afa6c51b14
Reconstructed micro-XRCT data set in 16 bit *.tif file format. 1944x1944x1425 voxels with the uniform voxel size of 24.9990 µm.
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