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1 to 10 of 30 Results
Nov 25, 2021 - Molecular Simulation
Markthaler, Daniel; Hansen, Niels, 2021, "Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'", https://doi.org/10.18419/darus-2104, DaRUS, V1
This dataset contains all relevant simulation input files (topologies, coordinates, simulation parameters), generated simulation output (final configurations, time series of collective variables) together with scripts used for set-up and analysis of the umbrella sampling and doub...
Nov 24, 2021 - tBME project
Hsueh, Han-Fang, 2021, "Code of the tBME method", https://doi.org/10.18419/darus-1836, DaRUS, V1
Code and data for the publication "Diagnosis of model errors with a sliding time-window Bayesian analysis" in Journal Water Resource Research (preprint https://arxiv.org/abs/2107.09399) . The folder "tau_plot" includes the files and data to generate the tBME analysis plots for Ca...
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_...
tBME project(Universität Stuttgart)
Nov 23, 2021Stochastic Simulation and Safety Research for Hydrosystems (LS3)
tBME project
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."
Oct 15, 2021 - PN 6
Zaverkin, Viktor; Holzmüller, David; Steinwart, Ingo; Kästner, Johannes, 2021, "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments", https://doi.org/10.18419/darus-2136, DaRUS, V1
Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found on GitLab
Oct 5, 2021 - PN 6-6
Tkachev, Gleb, 2021, "Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"", https://doi.org/10.18419/darus-2174, DaRUS, V1
We train a self-supervised siamese model that enables querying for similar behavior on spatiotemporal volumes. Here we provide the code and data needed to reproduce the representative figures of the paper. See the notes and the included readme file for details.
PN 6-6(Universität Stuttgart)
Sep 29, 2021PN 6
SimTech Project PN 6-6 "Machine Learning for Data-driven Visualization"
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...
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