Stuttgart Center for Simulation Science (SC SimTech)

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.

Publication Year: 2022

11 to 20 of 45 Results

Replication Data for: Geothermal-ML - predicting thermal plume from groundwater heat pumps Oct 26, 2022 - Projects without PN Affiliation Davis, Kyle; Schulte, Miriam, 2022, "Replication Data for: Geothermal-ML - predicting thermal plume from groundwater heat pumps", https://doi.org/10.18419/darus-3184, DaRUS, V1 This dataset provides all python3 code necessary to train convolutional neural networks built with pyTorch, as well as the data to train the networks. A README file is provided with instructions for accessing the training data, viewing the alread computed models, and all software...
Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework Mar 29, 2022 - PN 6 Holzmüller, David, 2022, "Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework", https://doi.org/10.18419/darus-1779, DaRUS, V1, UNF:6:aIyuHfDcWPT9LJvtkCge9w== [fileUNF] This dataset contains supplementary code for the paper Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework. The code is also provided on GitHub. Here, we additionally provide the runtime measurement data generated by the code, which...
REG-30 model to replicate simulation results for the GEO.KW project Oct 26, 2022 - Projects without PN Affiliation Davis, Kyle; Schulte, Miriam, 2022, "REG-30 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/darus-3195, DaRUS, V1 This data repository contains the REG-30 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs software and simulation setup. Instructions for building the spack environment and running the simulation are provided in the README.
PyPlant: A Python Framework for Cached Function Pipelines Jan 24, 2022 - PN 6-6 Tkachev, Gleb, 2022, "PyPlant: A Python Framework for Cached Function Pipelines", https://doi.org/10.18419/darus-2249, DaRUS, V1 PyPlant is a simple coroutine-based framework for writing data processing pipelines. PyPlant's goal is to simplify caching of intermediate results in the pipeline and avoid re-running expensive early stages of the pipeline, when only the later stages have changed.
Propioin Synthesis using Benzoin Aldolase Feb 15, 2022 - EnzymeML at work Spöring, Jan-Dirk, 2022, "Propioin Synthesis using Benzoin Aldolase", https://doi.org/10.18419/darus-2466, DaRUS, V1 Investigated was the ligation of two molecules propanal in organic conditions, catalysed by the benzoin aldolase, which was added in the form of lyophillised whole cells. The reaction was performed in triplicate, with 200 mM as the starting concentration of the propanal in all ca...
preCICE Distribution Version v2202.0 Apr 21, 2022 - Usability and Sustainability of Simulation Software Chourdakis, Gerasimos; Davis, Kyle; Desai, Ishaan; Rodenberg, Benjamin; Schneider, David; Simonis, Frédéric; Uekermann, Benjamin; Firmbach, Max; Jaust, Alexander; Lorenz, Christopher; Martin, Boris; Olesen, Mark; Ziya Koseomur, Oguz, 2022, "preCICE Distribution Version v2202.0", https://doi.org/10.18419/darus-2613, 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...
PN 4-7(Universität Stuttgart) May 16, 2022PN 4 Combining First Principles and Neural Network Models for Interpretable, High-Precision Multi-Step Predictions (InMotion)
PN 3-8(Universität Stuttgart) Jul 5, 2022PN 3 Use of physically-based surrogate models to accelerate the optimization of classical force fields and development of new reduced order models for transport properties based on entropy scaling. Machine-learned models for transport properties will be developed with an increasing da...
PN 2-6(Universität Stuttgart) Apr 19, 2022PN 2 Software-driven RDM (sdRDM), a generic and extensible bottom-up research data management concept and its application in biocatalysis and beyond.
PDEBench Pretrained Models Nov 30, 2023 - SciML PDE Benchmark Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Pretrained Models", https://doi.org/10.18419/darus-2987, DaRUS, V2 This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D...

Replication Data for: Geothermal-ML - predicting thermal plume from groundwater heat pumps

Oct 26, 2022 - Projects without PN Affiliation

Davis, Kyle; Schulte, Miriam, 2022, "Replication Data for: Geothermal-ML - predicting thermal plume from groundwater heat pumps", https://doi.org/10.18419/darus-3184, DaRUS, V1

This dataset provides all python3 code necessary to train convolutional neural networks built with pyTorch, as well as the data to train the networks. A README file is provided with instructions for accessing the training data, viewing the alread computed models, and all software...

Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework

Mar 29, 2022 - PN 6

Holzmüller, David, 2022, "Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework", https://doi.org/10.18419/darus-1779, DaRUS, V1, UNF:6:aIyuHfDcWPT9LJvtkCge9w== [fileUNF]

This dataset contains supplementary code for the paper Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework. The code is also provided on GitHub. Here, we additionally provide the runtime measurement data generated by the code, which...

REG-30 model to replicate simulation results for the GEO.KW project

Oct 26, 2022 - Projects without PN Affiliation

Davis, Kyle; Schulte, Miriam, 2022, "REG-30 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/darus-3195, DaRUS, V1

This data repository contains the REG-30 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs software and simulation setup. Instructions for building the spack environment and running the simulation are provided in the README.

PyPlant: A Python Framework for Cached Function Pipelines

Jan 24, 2022 - PN 6-6

Tkachev, Gleb, 2022, "PyPlant: A Python Framework for Cached Function Pipelines", https://doi.org/10.18419/darus-2249, DaRUS, V1

PyPlant is a simple coroutine-based framework for writing data processing pipelines. PyPlant's goal is to simplify caching of intermediate results in the pipeline and avoid re-running expensive early stages of the pipeline, when only the later stages have changed.

Propioin Synthesis using Benzoin Aldolase

Feb 15, 2022 - EnzymeML at work

Spöring, Jan-Dirk, 2022, "Propioin Synthesis using Benzoin Aldolase", https://doi.org/10.18419/darus-2466, DaRUS, V1

Investigated was the ligation of two molecules propanal in organic conditions, catalysed by the benzoin aldolase, which was added in the form of lyophillised whole cells. The reaction was performed in triplicate, with 200 mM as the starting concentration of the propanal in all ca...

preCICE Distribution Version v2202.0

Apr 21, 2022 - Usability and Sustainability of Simulation Software

Chourdakis, Gerasimos; Davis, Kyle; Desai, Ishaan; Rodenberg, Benjamin; Schneider, David; Simonis, Frédéric; Uekermann, Benjamin; Firmbach, Max; Jaust, Alexander; Lorenz, Christopher; Martin, Boris; Olesen, Mark; Ziya Koseomur, Oguz, 2022, "preCICE Distribution Version v2202.0", https://doi.org/10.18419/darus-2613, 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...

PN 4-7(Universität Stuttgart)

May 16, 2022PN 4

Combining First Principles and Neural Network Models for Interpretable, High-Precision Multi-Step Predictions (InMotion)

PN 3-8(Universität Stuttgart)

Jul 5, 2022PN 3

Use of physically-based surrogate models to accelerate the optimization of classical force fields and development of new reduced order models for transport properties based on entropy scaling. Machine-learned models for transport properties will be developed with an increasing da...

PN 2-6(Universität Stuttgart)

Apr 19, 2022PN 2

Software-driven RDM (sdRDM), a generic and extensible bottom-up research data management concept and its application in biocatalysis and beyond.

PDEBench Pretrained Models

Nov 30, 2023 - SciML PDE Benchmark

Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Pretrained Models", https://doi.org/10.18419/darus-2987, DaRUS, V2

This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D...

Add Data

Share Dataverse

Link Dataverse

Reset Modifications