Stuttgart Center for Simulation Science (SC SimTech)

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Subject: Computer and Information Science Deposit Date: 2022 Author Affiliation: Universität Stuttgart

1 to 10 of 17 Results

PDEBench Datasets Feb 13, 2024 - SciML PDE Benchmark Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8 This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...
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: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar Apr 5, 2023 - Projects without PN Affiliation Rettberg, Johannes; Wittwar, Dominik; Buchfink, Patrick; Brauchler, Alexander; Ziegler, Pascal; Fehr, Jörg; Haasdonk, Bernard, 2023, "Replication Data for: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar", https://doi.org/10.18419/darus-3248, DaRUS, V1 This dataset includes the system matrices in velocity formulation and a parallel coordinates plot of the sensitivity analysis from the paper titled "Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar". The sy...
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...
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 be...
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: In...
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 e...
Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network Nov 2, 2022 - PN 5-6 Praditia, Timothy; Karlbauer, Matthias; Otte, Sebastian; Oladyshkin, Sergey; Butz, Martin V.; Nowak, Wolfgang, 2022, "Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network", https://doi.org/10.18419/darus-3249, DaRUS, V1 This dataset contains diffusion-sorption data, generated with numerical simulation based on three different sorption isotherms, namely the linear, Freundlich, and Langmuir isotherms. This dataset is used to train, validate, and test all the deep learning models that are used in t...
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...
COM-4 model to replicate simulation results for the GEO.KW project Oct 26, 2022 - Projects without PN Affiliation Davis, Kyle; Schulte, Miriam, 2022, "COM-4 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/darus-3185, DaRUS, V1 This data repository contains the COM-4 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs simulation setup, spack build environment and spack build mirror to replicate the software build environment. A README file is provided, explaining the spack building...

PDEBench Datasets

Feb 13, 2024 - SciML PDE Benchmark

Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8

This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...

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: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar

Apr 5, 2023 - Projects without PN Affiliation

Rettberg, Johannes; Wittwar, Dominik; Buchfink, Patrick; Brauchler, Alexander; Ziegler, Pascal; Fehr, Jörg; Haasdonk, Bernard, 2023, "Replication Data for: Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar", https://doi.org/10.18419/darus-3248, DaRUS, V1

This dataset includes the system matrices in velocity formulation and a parallel coordinates plot of the sensitivity analysis from the paper titled "Port-Hamiltonian Fluid-Structure Interaction Modeling and Structure-Preserving Model Order Reduction of a Classical Guitar". The sy...

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...

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 be...

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: In...

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 e...

Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network

Nov 2, 2022 - PN 5-6

Praditia, Timothy; Karlbauer, Matthias; Otte, Sebastian; Oladyshkin, Sergey; Butz, Martin V.; Nowak, Wolfgang, 2022, "Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network", https://doi.org/10.18419/darus-3249, DaRUS, V1

This dataset contains diffusion-sorption data, generated with numerical simulation based on three different sorption isotherms, namely the linear, Freundlich, and Langmuir isotherms. This dataset is used to train, validate, and test all the deep learning models that are used in t...

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...

COM-4 model to replicate simulation results for the GEO.KW project

Oct 26, 2022 - Projects without PN Affiliation

Davis, Kyle; Schulte, Miriam, 2022, "COM-4 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/darus-3185, DaRUS, V1

This data repository contains the COM-4 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs simulation setup, spack build environment and spack build mirror to replicate the software build environment. A README file is provided, explaining the spack building...

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