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.

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

391 to 400 of 2,761 Results
Dec 20, 2024 - Publication: A novel geometry-informed drag term formulation for pseudo-3D Stokes simulations with varying apertures
Krach, David; Weinhardt, Felix; Wang, Mingfeng; Schneider, Martin; Class, Holger; Steeb, Holger, 2024, "Code and benchmarks for geometry-informed drag term computation for pseudo-3D Stokes simulations with varying apertures", https://doi.org/10.18419/DARUS-4313, DaRUS, V2
Content: This data set includes snapshots of the code used to compute the benchmarks and applications in Krach et al.(2024). All software tools provided enable the user to perform pseudo-3D Stokes simulations with a geometry-informed drag term using DuMux and to determine permeability, volumetric flux as well as local pressure and velocity fields f...
Gzip Archive - 110.2 KB - MD5: 9184f049d4cee0af1e10ea48529bf0f3
localdrag python module
Gzip Archive - 2.3 MB - MD5: 04abee75c9fb1dca64cdaa9b68cf28f8
Pseudo3D_Stokes DuMux submodule
Dec 19, 2024 - Evaporation-driven density instabilities in unsaturated porous media
Kiemle, Stefanie, 2024, "DuMuX code for modelling evaporation-driven density instabilities in unsaturated porous media", https://doi.org/10.18419/DARUS-4610, DaRUS, V1
This dataset contains the source code to reproduce the numerical simulations presented in Bringedal et al. Impact of saturation on evaporation-driven density instabilities in porous media: mathematical and numerical analysis (submitted), Transport in Porous Media, **TODO: add doi after acceptance**. The application allows to model the estimated ons...
Python Source Code - 4.1 KB - MD5: e2d1cea10ee7b67729335ba0d3c03fa6
Installation script
Gzip Archive - 99.6 KB - MD5: 06da7b6c13c74f3e6e7948cfa76d9012
Source code
Markdown Text - 4.4 KB - MD5: b1684f4702f786078f0b539c75815351
Instructions to install and use the module
Dec 13, 2024 - D03: Development and realisation of validation benchmarks
Kohlhaas, Rebecca; Morales Oreamuno, Maria Fernanda, 2024, "BayesValidRox 1.1.0", https://doi.org/10.18419/DARUS-4613, DaRUS, V1
Release 1.1.0 of BayesValidRox. BayesValidRox is an open-source python package that provides methods for surrogate modeling, Bayesian inference and model comparison. (2024-07-18)
Dec 13, 2024 - BayesValidRox 1.1.0
Gzip Archive - 140.9 KB - MD5: 37c66a1cecb9867545a7dec06da1d711
Nov 19, 2024 - Publication: A novel geometry-informed drag term formulation for pseudo-3D Stokes simulations with varying apertures
Krach, David; Weinhardt, Felix; Wang, Mingfeng; Schneider, Martin; Class, Holger; Steeb, Holger, 2024, "Results for pseudo-3D Stokes simulations with a geometry-informed drag term formulation for porous media with varying apertures", https://doi.org/10.18419/DARUS-4347, DaRUS, V1
Content: This data set includes all the necessary input data to fully replicate the benchmarks and applications in Krach et al.(2024). In addition, the results for all solvers are provided as raw simulation output as well as in condense form. Complete datasets: 01_CYLINDER, 02_SINGLE_PRECIPITATE, 03_SEGMENT1, 04_SEGMENT2, 05_SEGMENT3 Each data set...
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.