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1 to 10 of 26 Results

Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data Jun 18, 2021 - Modeling Strategies for Gas migration in Subsurface Banerjee, Ishani, 2021, "Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data", https://doi.org/10.18419/darus-1776, DaRUS, V1 This dataset contains modeling data used to obtain the results and figures in the manuscript: "Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data." In particular, the model realization data a...
Regime-and-memory model (RMM) Code Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty Gonzalez-Nicolas Alvarez, Ana, 2021, "Regime-and-memory model (RMM) Code", https://doi.org/10.18419/darus-2034, DaRUS, V1 We introduce a simple stochastic time-series model (regime-and-memory model, RMM) for concentrations in the river that accounts for fluctuating release and transport with memory, using an autocorrelation over time.One explicit parameter of our model represents the export regime....
Sampling Strategies of the Regime-and-memory model (RMM) Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty Gonzalez-Nicolas Alvarez, Ana, 2021, "Sampling Strategies of the Regime-and-memory model (RMM)", https://doi.org/10.18419/darus-2035, DaRUS, V1, UNF:6:JeAvfovoq369qtbASSmQjg== [fileUNF] This excel file includes the observation time, Q, concentration, and lag-time used by the sampling strategies. Types of sampling strategies: Time frequency sampling strategies. River discharge frequency sampling strategies. Low Q sampling strategies. High Q sampling strategies. L...
Code of the tBME method Nov 24, 2021 - tBME project Hsueh, Han-Fang, 2021, "Code of the tBME method", https://doi.org/10.18419/darus-1836, DaRUS, V1 Code and data for the publication "Diagnosis of model errors with a sliding time-window Bayesian analysis" in Journal Water Resource Research (preprint https://arxiv.org/abs/2107.09399) . The folder "tau_plot" includes the files and data to generate the tBME analysis plots for Ca...
Case Study Database for: Documenting Research Software in Engineering Science Mar 29, 2022 Hermann, Sibylle, 2022, "Case Study Database for: Documenting Research Software in Engineering Science", https://doi.org/10.18419/darus-2681, DaRUS, V1, UNF:6:b7kyHlt+OvbLE/xZr7JtHQ== [fileUNF] This dataset contains the collected data of a case study on the documentation of research software in the institutional everyday life of engineering scientists. All files beginning with "Notes" contain personal thoughts and transcripts. More detailed descriptions about the conten...
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...
Replication Data for: Radial basis function interpolation with partition of unity for PyRBF Oct 26, 2022 Davis, Kyle; Schulte, Miriam, 2022, "Replication Data for: Radial basis function interpolation with partition of unity for PyRBF", https://doi.org/10.18419/darus-3183, DaRUS, V1, UNF:6:n9rIOI84ZodNZYhB8p26GQ== [fileUNF] The dataset provides the PyRBF python code to perform partition of unity radial basis function interpolation. This includes all meshes in VTK format and a post processing folder to generate the figures from provided results. The README provides further instructions. All software...
REG-30 model to replicate simulation results for the GEO.KW project Oct 26, 2022 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.
COM-4 model to replicate simulation results for the GEO.KW project Oct 26, 2022 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...
Replication Data for: Geothermal-ML - predicting thermal plume from groundwater heat pumps Oct 26, 2022 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: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data

Jun 18, 2021 - Modeling Strategies for Gas migration in Subsurface

Banerjee, Ishani, 2021, "Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data", https://doi.org/10.18419/darus-1776, DaRUS, V1

This dataset contains modeling data used to obtain the results and figures in the manuscript: "Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data." In particular, the model realization data a...

Regime-and-memory model (RMM) Code

Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty

Gonzalez-Nicolas Alvarez, Ana, 2021, "Regime-and-memory model (RMM) Code", https://doi.org/10.18419/darus-2034, DaRUS, V1

We introduce a simple stochastic time-series model (regime-and-memory model, RMM) for concentrations in the river that accounts for fluctuating release and transport with memory, using an autocorrelation over time.One explicit parameter of our model represents the export regime....

Sampling Strategies of the Regime-and-memory model (RMM)

Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty

Gonzalez-Nicolas Alvarez, Ana, 2021, "Sampling Strategies of the Regime-and-memory model (RMM)", https://doi.org/10.18419/darus-2035, DaRUS, V1, UNF:6:JeAvfovoq369qtbASSmQjg== [fileUNF]

This excel file includes the observation time, Q, concentration, and lag-time used by the sampling strategies. Types of sampling strategies: Time frequency sampling strategies. River discharge frequency sampling strategies. Low Q sampling strategies. High Q sampling strategies. L...

Code of the tBME method

Nov 24, 2021 - tBME project

Hsueh, Han-Fang, 2021, "Code of the tBME method", https://doi.org/10.18419/darus-1836, DaRUS, V1

Code and data for the publication "Diagnosis of model errors with a sliding time-window Bayesian analysis" in Journal Water Resource Research (preprint https://arxiv.org/abs/2107.09399) . The folder "tau_plot" includes the files and data to generate the tBME analysis plots for Ca...

Case Study Database for: Documenting Research Software in Engineering Science

Mar 29, 2022

Hermann, Sibylle, 2022, "Case Study Database for: Documenting Research Software in Engineering Science", https://doi.org/10.18419/darus-2681, DaRUS, V1, UNF:6:b7kyHlt+OvbLE/xZr7JtHQ== [fileUNF]

This dataset contains the collected data of a case study on the documentation of research software in the institutional everyday life of engineering scientists. All files beginning with "Notes" contain personal thoughts and transcripts. More detailed descriptions about the conten...

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...

Replication Data for: Radial basis function interpolation with partition of unity for PyRBF

Oct 26, 2022

Davis, Kyle; Schulte, Miriam, 2022, "Replication Data for: Radial basis function interpolation with partition of unity for PyRBF", https://doi.org/10.18419/darus-3183, DaRUS, V1, UNF:6:n9rIOI84ZodNZYhB8p26GQ== [fileUNF]

The dataset provides the PyRBF python code to perform partition of unity radial basis function interpolation. This includes all meshes in VTK format and a post processing folder to generate the figures from provided results. The README provides further instructions. All software...

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

Oct 26, 2022

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.

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

Oct 26, 2022

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...

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

Oct 26, 2022

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...

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