Stuttgart Center for Simulation Science (SC SimTech)

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Subject: Physics

11 to 20 of 42 Results

BLinK(Universität Stuttgart) Jun 7, 2023Membranes Container for the BLinK project
Membranes(Universität Stuttgart) Jun 7, 2023PN 1-8 Dataverse containig material on lipid membranes and surfaces interactions
Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems May 26, 2023 - Materials Design Gubaev, Konstantin; Zaverkin, Viktor; Srinivasan, Prashanth; Duff, Andrew; Kästner, Johannes; Grabowski, Blazej, 2023, "Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems", https://doi.org/10.18419/darus-3516, DaRUS, V1 Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the datasets of structures in cfg and npz formats INCAR file which was used for VASP calculations python script f...
Data for: Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals May 12, 2023 - Materials Design Forslund, Axel; Jung, Jong Hyun; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals", https://doi.org/10.18419/darus-3339, DaRUS, V1 Data for the publication Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals, Phys. Rev. B 107, 174309 (2023). This data set contains - the training sets (VAS...
PN 3-11(Universität Stuttgart) Feb 28, 2023PN 3 Biological Molecular Dynamics Simulations
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 checkpoint...
Simulation Data from Motorcycle Sensors in Operational and Crash Scenarios Jan 17, 2023 - PN 7-6 Rodegast, Philipp; Maier, Steffen; Kneifl, Jonas; Fehr, Jörg, 2023, "Simulation Data from Motorcycle Sensors in Operational and Crash Scenarios", https://doi.org/10.18419/darus-3301, DaRUS, V1, UNF:6:rnJlYpzgwi2nYAtNG7jBtA== [fileUNF] This dataset provides time-dependent simulation results from high-fidelity motorcycle body crash scenarios. The set contains the angular as well as linear positions, velocities, and accelerations of different parts of the motorcycle. In addition, force and contact sensor signals...
MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks Dec 16, 2022 - demoa Wochner, Isabell; Schmitt, Syn, 2022, "MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks", https://doi.org/10.18419/darus-3268, DaRUS, V1 This code allows you reproduce the optimal control and model predictive control results of the paper: "Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks" by Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt an...
demoa-base: a biophysics simulator for muscle-driven motion Nov 30, 2022 - demoa Schmitt, Syn, 2022, "demoa-base: a biophysics simulator for muscle-driven motion", https://doi.org/10.18419/darus-2550, DaRUS, V4 For more information, such as installation, requirements and user guide, please see the demoa-manual.pdf
gspine: A Human Spine Model Built Using Literature Data Oct 6, 2022 - demoa Hammer, Maria; Riede, Julia Maria; Meszaros-Beller, Laura; Schmitt, Syn, 2022, "gspine: A Human Spine Model Built Using Literature Data", https://doi.org/10.18419/darus-2814, DaRUS, V3 A fully articulating human spine model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. The model is prepared to run muscle-driven simulation using a simple biological motor control model. The file...

BLinK(Universität Stuttgart)

Jun 7, 2023Membranes

Container for the BLinK project

Membranes(Universität Stuttgart)

Jun 7, 2023PN 1-8

Dataverse containig material on lipid membranes and surfaces interactions

Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems

May 26, 2023 - Materials Design

Gubaev, Konstantin; Zaverkin, Viktor; Srinivasan, Prashanth; Duff, Andrew; Kästner, Johannes; Grabowski, Blazej, 2023, "Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems", https://doi.org/10.18419/darus-3516, DaRUS, V1

Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the datasets of structures in cfg and npz formats INCAR file which was used for VASP calculations python script f...

Data for: Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals

May 12, 2023 - Materials Design

Forslund, Axel; Jung, Jong Hyun; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals", https://doi.org/10.18419/darus-3339, DaRUS, V1

Data for the publication Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals, Phys. Rev. B 107, 174309 (2023). This data set contains - the training sets (VAS...

PN 3-11(Universität Stuttgart)

Feb 28, 2023PN 3

Biological Molecular Dynamics Simulations

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 checkpoint...

Simulation Data from Motorcycle Sensors in Operational and Crash Scenarios

Jan 17, 2023 - PN 7-6

Rodegast, Philipp; Maier, Steffen; Kneifl, Jonas; Fehr, Jörg, 2023, "Simulation Data from Motorcycle Sensors in Operational and Crash Scenarios", https://doi.org/10.18419/darus-3301, DaRUS, V1, UNF:6:rnJlYpzgwi2nYAtNG7jBtA== [fileUNF]

This dataset provides time-dependent simulation results from high-fidelity motorcycle body crash scenarios. The set contains the angular as well as linear positions, velocities, and accelerations of different parts of the motorcycle. In addition, force and contact sensor signals...

MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks

Dec 16, 2022 - demoa

Wochner, Isabell; Schmitt, Syn, 2022, "MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks", https://doi.org/10.18419/darus-3268, DaRUS, V1

This code allows you reproduce the optimal control and model predictive control results of the paper: "Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks" by Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt an...

demoa-base: a biophysics simulator for muscle-driven motion

Nov 30, 2022 - demoa

Schmitt, Syn, 2022, "demoa-base: a biophysics simulator for muscle-driven motion", https://doi.org/10.18419/darus-2550, DaRUS, V4

For more information, such as installation, requirements and user guide, please see the demoa-manual.pdf

gspine: A Human Spine Model Built Using Literature Data

Oct 6, 2022 - demoa

Hammer, Maria; Riede, Julia Maria; Meszaros-Beller, Laura; Schmitt, Syn, 2022, "gspine: A Human Spine Model Built Using Literature Data", https://doi.org/10.18419/darus-2814, DaRUS, V3

A fully articulating human spine model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. The model is prepared to run muscle-driven simulation using a simple biological motor control model. The file...

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