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Subject: Earth and Environmental Sciences Publication Year: 2022

1 to 10 of 36 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...
Pressure and volumetric flux measurements intended to scale relative permeability under steady state, co-flow conditions, in a PDMS micromodel Sep 12, 2023 - Publication: Microfluidic experiments Karadimitriou, Nikolaos; Steeb, Holger; Valavanides, Marios, 2022, "Pressure and volumetric flux measurements intended to scale relative permeability under steady state, co-flow conditions, in a PDMS micromodel", https://doi.org/10.18419/darus-2816, DaRUS, V2 The current repository contains raw data collected during a systematic laboratory study, examining the flow rate dependency of steady-state, co-injection of two-immiscible fluids within a microfluidic pore network model. The study is presented in the paper by Karadimitriou et al....
Institute of Microbiology(Universität Stuttgart) Dec 20, 2022
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: Flow in Porous Media with Fractures of Varying Aperture Oct 28, 2022 - B03: Heterogeneous multi-scale methods for two-phase flow in dynamically fracturing porous media Burbulla, Samuel; Hörl, Maximilian; Rohde, Christian, 2022, "Replication Data for: Flow in Porous Media with Fractures of Varying Aperture", https://doi.org/10.18419/darus-3227, DaRUS, V1 This data set contains the simulation data for the results presented in [S. Burbulla, M. Hörl, and C. Rohde (2022). "Flow in Porous Media with Fractures of Varying Aperture." Submitted for publication, https://doi.org/10.48550/arXiv.2207.09301]. We consider the numerical solution...
Source Code for: Flow in Porous Media with Fractures of Varying Aperture Oct 28, 2022 - B03: Heterogeneous multi-scale methods for two-phase flow in dynamically fracturing porous media Burbulla, Samuel; Hörl, Maximilian; Rohde, Christian, 2022, "Source Code for: Flow in Porous Media with Fractures of Varying Aperture", https://doi.org/10.18419/darus-3012, DaRUS, V1 Python source code to replicate the results in [S. Burbulla, M. Hörl, and C. Rohde (2022). "Flow in Porous Media with Fractures of Varying Aperture." Submitted for publication, https://doi.org/10.48550/arXiv.2207.09301]. The contained Python package "mmdgpy" is an implementation...
DuMux(Universität Stuttgart) Oct 27, 2022Hydromechanics and Modelling of Hydrosystems DuMux, https://dumux.org/, is short for Dune for Multi-{Phase, Component, Scale, Physics, …} flow and transport in porous media a free and open-source simulator for flow and transport processes in porous media a research code written in C++ based on Dune (Distributed and Unified...
Hydromechanics and Modelling of Hydrosystems(Universität Stuttgart) Oct 27, 2022Institute for Modelling Hydraulic and Environmental Systems (IWS) The Department of Hydromechanics and Modelling of Hydrosystems is one out of five departments of the Institute for Modelling Hydraulic and Environmental Systems (IWS).
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...

Pressure and volumetric flux measurements intended to scale relative permeability under steady state, co-flow conditions, in a PDMS micromodel

Sep 12, 2023 - Publication: Microfluidic experiments

Karadimitriou, Nikolaos; Steeb, Holger; Valavanides, Marios, 2022, "Pressure and volumetric flux measurements intended to scale relative permeability under steady state, co-flow conditions, in a PDMS micromodel", https://doi.org/10.18419/darus-2816, DaRUS, V2

The current repository contains raw data collected during a systematic laboratory study, examining the flow rate dependency of steady-state, co-injection of two-immiscible fluids within a microfluidic pore network model. The study is presented in the paper by Karadimitriou et al....

Institute of Microbiology(Universität Stuttgart)

Dec 20, 2022

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: Flow in Porous Media with Fractures of Varying Aperture

Oct 28, 2022 - B03: Heterogeneous multi-scale methods for two-phase flow in dynamically fracturing porous media

Burbulla, Samuel; Hörl, Maximilian; Rohde, Christian, 2022, "Replication Data for: Flow in Porous Media with Fractures of Varying Aperture", https://doi.org/10.18419/darus-3227, DaRUS, V1

This data set contains the simulation data for the results presented in [S. Burbulla, M. Hörl, and C. Rohde (2022). "Flow in Porous Media with Fractures of Varying Aperture." Submitted for publication, https://doi.org/10.48550/arXiv.2207.09301]. We consider the numerical solution...

Source Code for: Flow in Porous Media with Fractures of Varying Aperture

Oct 28, 2022 - B03: Heterogeneous multi-scale methods for two-phase flow in dynamically fracturing porous media

Burbulla, Samuel; Hörl, Maximilian; Rohde, Christian, 2022, "Source Code for: Flow in Porous Media with Fractures of Varying Aperture", https://doi.org/10.18419/darus-3012, DaRUS, V1

Python source code to replicate the results in [S. Burbulla, M. Hörl, and C. Rohde (2022). "Flow in Porous Media with Fractures of Varying Aperture." Submitted for publication, https://doi.org/10.48550/arXiv.2207.09301]. The contained Python package "mmdgpy" is an implementation...

DuMux(Universität Stuttgart)

Oct 27, 2022Hydromechanics and Modelling of Hydrosystems

DuMux, https://dumux.org/, is short for Dune for Multi-{Phase, Component, Scale, Physics, …} flow and transport in porous media a free and open-source simulator for flow and transport processes in porous media a research code written in C++ based on Dune (Distributed and Unified...

Hydromechanics and Modelling of Hydrosystems(Universität Stuttgart)

Oct 27, 2022Institute for Modelling Hydraulic and Environmental Systems (IWS)

The Department of Hydromechanics and Modelling of Hydrosystems is one out of five departments of the Institute for Modelling Hydraulic and Environmental Systems (IWS).

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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