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1 to 6 of 6 Results
Nov 24, 2021 - PN 1-6
Schulz, Sebastian; Bringedal, Carina; Ackermann, Sina, 2021, "Code for relative permeabilities for two-phase flow between parallel plates with slip conditions", https://doi.org/10.18419/darus-2241, DaRUS, V1
This MATLAB code calculates relative permeabilities of two fluids flowing between two parallel plates, depending on their viscosities, saturation and boundary conditions at the top and bottom plates. The underlying assumptions behind the derivation are shown in the pdf "overview_...
PN 1-6(Universität Stuttgart)
Nov 22, 2021PN 1
SimTech Project PN 1-6 "Upscaling of two-phase porous media flow based on fluid morphology."
Sep 27, 2021 - Usability and Sustainability of Simulation Software
Chourdakis, Gerasimos; Davis, Kyle; Rodenberg, Benjamin; Schulte, Miriam; Simonis, Frédéric; Uekermann, Benjamin; Abrams, Georg; Bungartz, Hans-Joachim; Cheun Yau, Lucia; Desai, Ishaan; Eder, Konrad; Hertrich, Richard; Lindner, Florian; Rusch, Alexander; Sashko, Dmytro; Schneider, David; Totounferoush, Amin; Volland, Dominik; Vollmer, Peter; Ziya Koseomur, Oguz, 2021, "preCICE Distribution Version v2104.0", https://doi.org/10.18419/darus-2125, DaRUS, V1
The preCICE distribution is the larger ecosystem around preCICE, which includes the core library, language bindings, adapters for popular solvers, tutorials, and vagrant files to prepare a virtual machine image. The compressed source files of this data set are only meant to archi...
May 21, 2021 - PN 4-4
Eschmann, Hannes, 2021, "A Data Set for Research on Data-based Methods for an Omnidirectional Mobile Robot", https://doi.org/10.18419/darus-1845, DaRUS, V1
The intend of this data set is the cooperation within SimTech. It will be particularly interesting for data-based modeling and control which is a key area of the research of project network 4. We are proud to provide real-world data, which is essential for the benchmark of any da...
PN 4-4(Institute of Engineering and Computational Mechanics, Universität Stuttgart)
May 10, 2021PN 4
Bridging the gap between theoretic research in distributed and learning-based model predictive control and multi-agent applications.
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