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Subject: Earth and Environmental Sciences Deposit Date: 2022

1 to 8 of 8 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...
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...
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 Environmen...
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: The Method of Forced Probabilities: a Computation Trick for Bayesian Model Evidence Oct 26, 2022 - Modeling Strategies for Gas migration in Subsurface Banerjee, Ishani; Walter, Peter, 2022, "Replication Data for: The Method of Forced Probabilities: a Computation Trick for Bayesian Model Evidence", https://doi.org/10.18419/darus-2815, DaRUS, V1 This dataset contains the codes used for implementing the method of forced probabilities of the manuscript: The Method of Forced Probabilities: A Computation Trick for Bayesian Model Evidence. Here, one can find the codes of implementation of the trick on stochastic invasion perc...

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...

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...

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 Environmen...

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: The Method of Forced Probabilities: a Computation Trick for Bayesian Model Evidence

Oct 26, 2022 - Modeling Strategies for Gas migration in Subsurface

Banerjee, Ishani; Walter, Peter, 2022, "Replication Data for: The Method of Forced Probabilities: a Computation Trick for Bayesian Model Evidence", https://doi.org/10.18419/darus-2815, DaRUS, V1

This dataset contains the codes used for implementing the method of forced probabilities of the manuscript: The Method of Forced Probabilities: A Computation Trick for Bayesian Model Evidence. Here, one can find the codes of implementation of the trick on stochastic invasion perc...

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