Stuttgart Center for Simulation Science (SC SimTech)

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111 to 120 of 213 Results

Molecular simulation scripts for bulk solutions Mar 8, 2023 - NMR investigation of water confined by salt interface Gravelle, Simon; Holm, Christian; Schlaich, Alexander, 2023, "Molecular simulation scripts for bulk solutions", https://doi.org/10.18419/DARUS-3179, DaRUS, V1 GROMACS molecular simulation input files for bulk solutions of NaCl and Na2SO4. Initial configuration with different salt concentration can be generated using the Python script ConfigurationGenerator.py, and successive GROMACS runs can be performed by running the runall.sh Bash script.
Interface Preserving Moving Mesh (Code) Mar 8, 2023 - Projects without PN Affiliation Alkämper, Maria; Magiera, Jim M., 2022, "Interface Preserving Moving Mesh (Code)", https://doi.org/10.18419/DARUS-1671, DaRUS, V2 Open source implementation in C++ for an interface preserving moving mesh in 2d and 3d using CGAL Delaunay triangulations. The time-dependent computational mesh allows for large point deformations while preserving a lower dimensional interface surface. See README.md for more information.
Replication Data for phase-field contributions in level-set comparison study Mar 2, 2023 - PN 1-6 Kelm, Mathis; Bringedal, Carina; Flemisch, Bernd, 2023, "Replication Data for phase-field contributions in level-set comparison study", https://doi.org/10.18419/DARUS-3359, DaRUS, V1, UNF:6:MsNXqcARspF5yuVdFLKT0Q== [fileUNF] Primary and post-processed simulation data and visualization tools to reproduce the phase-field results presented in the related publication. The folders "simulation" and "effective_quantities" contain primary simulation results obtained with the code published in the DuMux-pub module Kelm2022a and post-processed effective quantities obtained using...
Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials Feb 20, 2023 - PN 6 Zaverkin, Viktor; Holzmüller, David; Bonfirraro, Luca; Kästner, Johannes, 2023, "Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials", https://doi.org/10.18419/DARUS-3299, DaRUS, V1 Pre-trained and fine-tuned ANI models using the Gaussian Moments Neural Network (GM-NN) approach. Code for GM-NN implemented within the Tensorflow framework, including the respective documentation and tutorials, can be found on GitLab. The data represents TensorFlow v2 checkpoints and stores the metadata for the checkpoint and parameters for the mo...
Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator Feb 15, 2023 - PN 5 Kohlhaas, Rebecca; Kröker, Ilja; Oladyshkin, Sergey; Nowak, Wolfgang, 2023, "Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator", https://doi.org/10.18419/DARUS-2829, DaRUS, V1 This folder contains the code for the aMR-PC toolbox by Ilja Kröker in the version used for the code in GALMAP_code. This toolbox was also used for Kröker et al. 2022 Link to current version of the toolbox here Data This folder contains inputs and simulated outputs of the CO_2 benchmark from here and referenced in Köppel et al. 2019 There are a set...
Code for: Seasonal Dynamics of Gaseous CO2 Concentrations in a Karst Cave Correspond With Aqueous Concentrations in a Stagnant Water Column Feb 13, 2023 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media Keim, Leon; Class, Holger; Schirmer, Larissa; Strauch, Bettina; Wendel, Kai; Zimmer, Martin, 2023, "Code for: Seasonal Dynamics of Gaseous CO2 Concentrations in a Karst Cave Correspond With Aqueous Concentrations in a Stagnant Water Column", https://doi.org/10.18419/DARUS-3276, DaRUS, V1 This dataset contains the DuMux code for the simulations in https://doi.org/10.3390/geosciences13020051 For the detailed list of software used, please have a look at the file install_class2023.sh. To run the simulations at your own computer, please conduct the following steps: Install docker for example in ubuntu . Make sure you can run docker with...
Data for: Measurement Campaign of Gaseous CO2 Concentrations in a Karst Cave with Aqueous Concentrations in a Stagnant Water Column 2021-2022. Feb 13, 2023 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media Keim, Leon; Class, Holger; Schirmer, Larissa; Wendel, Kai; Strauch, Bettina; Zimmer, Martin, 2023, "Data for: Measurement Campaign of Gaseous CO2 Concentrations in a Karst Cave with Aqueous Concentrations in a Stagnant Water Column 2021-2022.", https://doi.org/10.18419/DARUS-3271, DaRUS, V1 This dataset contains data generated during the measurement campaign inside the karst cave. The CO2 sensors in the cave air will continue to measure (as of Feb. 2023). For details on the site etc. see https://doi.org/10.3390/geosciences13020051 To create the graphs in the Class et al. 2023 Download cave-data.tar.xz, make sure you have the dependenc...
Continuum-mechanical Forward Simulation Results of a Human Upper-limb Model Under Varying Muscle Activations Jan 30, 2023 - PN 7-6 Kneifl, Jonas; Rosin, David; Avci, Okan; Röhrle, Oliver; Fehr, Jörg, 2023, "Continuum-mechanical Forward Simulation Results of a Human Upper-limb Model Under Varying Muscle Activations", https://doi.org/10.18419/DARUS-3302, DaRUS, V1 This dataset provides simulation results from a high-fidelity human upper-arm finite element model under varying muscle activations and an example script to load the data. The upper arm model consists of the bones of the radius and ulna for the forearm and the humerus for the upper arm. The elbow joint that connects them is modeled as a simple hing...
DuMux 3.6.0 Jan 26, 2023 - DuMux Kelm, Mathis; Ackermann, Sina; Buntic, Ivan; Coltman, Edward; Flemisch, Bernd; Gläser, Dennis; Grüninger, Christoph; Heck, Katharina; Hommel, Johannes; Keim, Leon; Kiemle, Stefanie; Koch, Timo; Lipp, Melanie; Schneider, Martin; Schollenberger, Theresa; Stadler, Leopold; Utz, Martin; Veyskarami, Maziar; Wang, Yue; Wendel, Kai; Werner, David; Wu, Hanchuan, 2023, "DuMux 3.6.0", https://doi.org/10.18419/DARUS-3247, DaRUS, V1 Release 3.6.0 of DuMux, DUNE for Multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media. DuMux is a free and open-source simulator for flow and transport processes in and around porous media. It is based on the Distributed and Unified Numerics Environment DUNE.
Experiment Videos of the Force-Based Non-Prehensile Cooperative Transportation of Objects with Mobile Robots Jan 25, 2023 - PN 4-4 Rosenfelder, Mario; Ebel, Henrik; Eberhard, Peter, 2023, "Experiment Videos of the Force-Based Non-Prehensile Cooperative Transportation of Objects with Mobile Robots", https://doi.org/10.18419/DARUS-3331, DaRUS, V1 The videos provided show two experimental results of cooperative object transportation using lightweight omnidirectional mobile robots. In particular, the mobile robots shall transport two different polygonal, but non-convex, objects along predefined paths. No central decision entity is employed; the tasks are accomplished in a purely distributed m...

Molecular simulation scripts for bulk solutions

Mar 8, 2023 - NMR investigation of water confined by salt interface

Gravelle, Simon; Holm, Christian; Schlaich, Alexander, 2023, "Molecular simulation scripts for bulk solutions", https://doi.org/10.18419/DARUS-3179, DaRUS, V1

GROMACS molecular simulation input files for bulk solutions of NaCl and Na2SO4. Initial configuration with different salt concentration can be generated using the Python script ConfigurationGenerator.py, and successive GROMACS runs can be performed by running the runall.sh Bash script.

Interface Preserving Moving Mesh (Code)

Mar 8, 2023 - Projects without PN Affiliation

Alkämper, Maria; Magiera, Jim M., 2022, "Interface Preserving Moving Mesh (Code)", https://doi.org/10.18419/DARUS-1671, DaRUS, V2

Open source implementation in C++ for an interface preserving moving mesh in 2d and 3d using CGAL Delaunay triangulations. The time-dependent computational mesh allows for large point deformations while preserving a lower dimensional interface surface. See README.md for more information.

Replication Data for phase-field contributions in level-set comparison study

Mar 2, 2023 - PN 1-6

Kelm, Mathis; Bringedal, Carina; Flemisch, Bernd, 2023, "Replication Data for phase-field contributions in level-set comparison study", https://doi.org/10.18419/DARUS-3359, DaRUS, V1, UNF:6:MsNXqcARspF5yuVdFLKT0Q== [fileUNF]

Primary and post-processed simulation data and visualization tools to reproduce the phase-field results presented in the related publication. The folders "simulation" and "effective_quantities" contain primary simulation results obtained with the code published in the DuMux-pub module Kelm2022a and post-processed effective quantities obtained using...

Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials

Feb 20, 2023 - PN 6

Zaverkin, Viktor; Holzmüller, David; Bonfirraro, Luca; Kästner, Johannes, 2023, "Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials", https://doi.org/10.18419/DARUS-3299, DaRUS, V1

Pre-trained and fine-tuned ANI models using the Gaussian Moments Neural Network (GM-NN) approach. Code for GM-NN implemented within the Tensorflow framework, including the respective documentation and tutorials, can be found on GitLab. The data represents TensorFlow v2 checkpoints and stores the metadata for the checkpoint and parameters for the mo...

Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator

Feb 15, 2023 - PN 5

Kohlhaas, Rebecca; Kröker, Ilja; Oladyshkin, Sergey; Nowak, Wolfgang, 2023, "Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator", https://doi.org/10.18419/DARUS-2829, DaRUS, V1

This folder contains the code for the aMR-PC toolbox by Ilja Kröker in the version used for the code in GALMAP_code. This toolbox was also used for Kröker et al. 2022 Link to current version of the toolbox here Data This folder contains inputs and simulated outputs of the CO_2 benchmark from here and referenced in Köppel et al. 2019 There are a set...

Code for: Seasonal Dynamics of Gaseous CO2 Concentrations in a Karst Cave Correspond With Aqueous Concentrations in a Stagnant Water Column

Feb 13, 2023 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media

Keim, Leon; Class, Holger; Schirmer, Larissa; Strauch, Bettina; Wendel, Kai; Zimmer, Martin, 2023, "Code for: Seasonal Dynamics of Gaseous CO2 Concentrations in a Karst Cave Correspond With Aqueous Concentrations in a Stagnant Water Column", https://doi.org/10.18419/DARUS-3276, DaRUS, V1

This dataset contains the DuMux code for the simulations in https://doi.org/10.3390/geosciences13020051 For the detailed list of software used, please have a look at the file install_class2023.sh. To run the simulations at your own computer, please conduct the following steps: Install docker for example in ubuntu . Make sure you can run docker with...

Data for: Measurement Campaign of Gaseous CO2 Concentrations in a Karst Cave with Aqueous Concentrations in a Stagnant Water Column 2021-2022.

Feb 13, 2023 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media

Keim, Leon; Class, Holger; Schirmer, Larissa; Wendel, Kai; Strauch, Bettina; Zimmer, Martin, 2023, "Data for: Measurement Campaign of Gaseous CO2 Concentrations in a Karst Cave with Aqueous Concentrations in a Stagnant Water Column 2021-2022.", https://doi.org/10.18419/DARUS-3271, DaRUS, V1

This dataset contains data generated during the measurement campaign inside the karst cave. The CO2 sensors in the cave air will continue to measure (as of Feb. 2023). For details on the site etc. see https://doi.org/10.3390/geosciences13020051 To create the graphs in the Class et al. 2023 Download cave-data.tar.xz, make sure you have the dependenc...

Continuum-mechanical Forward Simulation Results of a Human Upper-limb Model Under Varying Muscle Activations

Jan 30, 2023 - PN 7-6

Kneifl, Jonas; Rosin, David; Avci, Okan; Röhrle, Oliver; Fehr, Jörg, 2023, "Continuum-mechanical Forward Simulation Results of a Human Upper-limb Model Under Varying Muscle Activations", https://doi.org/10.18419/DARUS-3302, DaRUS, V1

This dataset provides simulation results from a high-fidelity human upper-arm finite element model under varying muscle activations and an example script to load the data. The upper arm model consists of the bones of the radius and ulna for the forearm and the humerus for the upper arm. The elbow joint that connects them is modeled as a simple hing...

DuMux 3.6.0

Jan 26, 2023 - DuMux

Kelm, Mathis; Ackermann, Sina; Buntic, Ivan; Coltman, Edward; Flemisch, Bernd; Gläser, Dennis; Grüninger, Christoph; Heck, Katharina; Hommel, Johannes; Keim, Leon; Kiemle, Stefanie; Koch, Timo; Lipp, Melanie; Schneider, Martin; Schollenberger, Theresa; Stadler, Leopold; Utz, Martin; Veyskarami, Maziar; Wang, Yue; Wendel, Kai; Werner, David; Wu, Hanchuan, 2023, "DuMux 3.6.0", https://doi.org/10.18419/DARUS-3247, DaRUS, V1

Release 3.6.0 of DuMux, DUNE for Multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media. DuMux is a free and open-source simulator for flow and transport processes in and around porous media. It is based on the Distributed and Unified Numerics Environment DUNE.

Experiment Videos of the Force-Based Non-Prehensile Cooperative Transportation of Objects with Mobile Robots

Jan 25, 2023 - PN 4-4

Rosenfelder, Mario; Ebel, Henrik; Eberhard, Peter, 2023, "Experiment Videos of the Force-Based Non-Prehensile Cooperative Transportation of Objects with Mobile Robots", https://doi.org/10.18419/DARUS-3331, DaRUS, V1

The videos provided show two experimental results of cooperative object transportation using lightweight omnidirectional mobile robots. In particular, the mobile robots shall transport two different polygonal, but non-convex, objects along predefined paths. No central decision entity is employed; the tasks are accomplished in a purely distributed m...

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