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1 to 10 of 18 Results
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...
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...
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.
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...
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...
Oct 14, 2022 - 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, V2
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...
Jun 21, 2022 - 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, V1
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...
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...
SciML PDE Benchmark(Universität Stuttgart)
Mar 23, 2022
This is a benchmark suite of PDE simulations comprising data for testing the performance of novel simulation or emulation methods against classical simulations.
Jan 27, 2022
Alkämper, Maria; Magiera, Jim M., 2022, "Interface Preserving Moving Mesh (Code)", https://doi.org/10.18419/darus-1671, DaRUS, V1
Open source implementation in C++ for an interface preserving moving mesh in 2d and 3d using CGAL Delaunay triangulations. The time-dependent computational mesh allows for large point deformations while preserving a lower dimensional interface surface. See README.md for more info...
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