11 to 20 of 100 Results
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... |
Nov 17, 2023 - PN 7-6
Kneifl, Jonas; Fehr, Jörg, 2023, "Crash Simulations of a Racing Kart's Structural Frame Colliding against a Rigid Wall", https://doi.org/10.18419/darus-3789, DaRUS, V1
Crash Simulations of a Racing Kart Frame Model This dataset contains results for several crash simulations of the frame of a racing kart colliding against a rigid wall. The wall and the frame itself are modeled as finite element models, implemented in the commercial software tool... |
Oct 11, 2023 - NMR insights into nanoconfined water using the surface exchange model
Gravelle, Simon, 2023, "Molecular simulation scripts for slit nanopores with tunable hydrophilicity", https://doi.org/10.18419/darus-3732, DaRUS, V1
GROMACS molecular simulation input files for slit nanopores filled with liquid water. Initial configuration can be generated using the Python script build_system.py. Use the bash script run_gmx.sh to run GROMACS. See the README.md file. |
Oct 1, 2023C01: A Lattice-Boltzmann investigation of two-phase electrolyte flow in porous structures with morphology alterations and tunable interfacial wetting behaviour
Molecular dynamics input scripts for GROMACS, and data analysis scripts in Python. |
Aug 24, 2023 - Holm group
Tovey, Samuel; Krippendorf, Sven; Nikolaou, Konstantin; Holm, Christian, 2023, "Scripts and Data for "Towards a phenomenological understanding of neural networks: data"", https://doi.org/10.18419/darus-3691, DaRUS, V1
Data and scripts to reproduce the plots in the paper. Data is separated into two directories: Surfaces: All data for rebuilding the surfaces rnd-plots: Data to reproduce the rnd plots The scripts, once run, will produce the plots in the paper. |
Aug 9, 2023 - Institute for Theoretical Physics IV
Speck, Thomas; Lemcke, Simon; Wand, Michael; Appeldorn, Jörn H., 2023, "Supplementary material for 'Towards a structural identification of metastable molecular conformations'", https://doi.org/10.18419/darus-3333, DaRUS, V2
This dataset contains simulation input files for GROMACS (topologies, index, simulation parameters, starting frames, run script) to be able to reproduce the data in the mentioned publication. The generated simulation trajectories are given and some processed data: The end-to-end... |
Aug 4, 2023 - Walking Model
Bunz, Elsa; Häufle, Daniel F. B.; Remy, C. David; Schmitt, Syn, 2023, "Experimental results for Bioinspired Preactivation Reflex Increases Robustness of Walking on Rough Terrain", https://doi.org/10.18419/darus-3492, DaRUS, V1
This dataset contains the experimental results and postprocessing script (Matlab, Mathworks, Natick, MA) to obtain the plots and results described in the paper "Bioinspired Preactivation Reflex Increases Robustness of Walking on Rough Terrain" by Elsa K. Bunz, Daniel F.B. Haeufle... |
Aug 2, 2023 - Institute of Aerospace Thermodynamics
Steigerwald, Jonas, 2023, "Numerical Data of Marangoni Test Case from "Visual Analysis of Interface Deformation in Multiphase Flow"", https://doi.org/10.18419/darus-3143, DaRUS, V1
This dataset contains the numerical data of the Marangoni convection test case from the study "Visual Analysis of Interface Deformation in Multiphase Flow". In the two investigated scenarios, a water drop coalesce with an ethanol drop. In one case, solutocapillary driven flow phe... |
Jun 27, 2023 - Scientific Computing
Pollinger, Theresa, 2023, "Replication Data for: Leveraging the compute power of two HPC systems for higher-dimensional grid-based simulations with the widely-distributed sparse grid combination technique", https://doi.org/10.18419/darus-3393, DaRUS, V1
We ran different fractions of the combination technique scenario described in the publication, also widely-distributed between the two machines SuperMUC-NG (file suffix `_ng`) and Hawk (file suffix `_hawk`). The dataset contains input files to generate the scenarios on the respec... |