591 to 600 of 1,845 Results
May 26, 2023 - Materials Design
Gubaev, Konstantin; Zaverkin, Viktor; Srinivasan, Prashanth; Duff, Andrew; Kästner, Johannes; Grabowski, Blazej, 2023, "Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems", https://doi.org/10.18419/DARUS-3516, DaRUS, V1
Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the datasets of structures in cfg and npz formats INCAR file which was used for VASP calculations python script for reading npz format These are essentially the 2-, 3-, and 4-componen... |
Schmitt, Marvin, 2023, "Replication Code for: Meta-Uncertainty in Bayesian Model Comparison", https://doi.org/10.18419/DARUS-3514, DaRUS, V1, UNF:6:zUDr3KGdcaDCy+jFtcz8lA== [fileUNF]
This dataverse contains the code for the paper Meta-Uncertainty in Bayesian Model Comparison: https://doi.org/10.48550/arXiv.2210.07278 Note that the R code is structured as a package, thus requiring a local installation with subsequent loading via library(MetaUncertaintyPaper). The experiments from the accompanying paper (see below) are implemente... |
May 23, 2023 - Institute of Geodesy
Tourian, Mohammad J., 2023, "Data for: Current availability and distribution of Congo basin's freshwater resources", https://doi.org/10.18419/DARUS-3377, DaRUS, V2
The Congo Basin is of global significance for biodiversity and the water and carbon cycles. However, its freshwater availability remains highly unknown. Here, we leverage two decades of satellite and in situ observations to develop a new method that characterizes the relationship between Drainable Water Storage Anomaly (DWSA) and river discharge ac... |
May 15, 2023 - PN 4-7
Baier, Alexandra; Frank, Daniel, 2023, "deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning", https://doi.org/10.18419/DARUS-3455, DaRUS, V1
deepsysid is a system identification toolkit for multistep prediction using deep learning and hybrid methods. The toolkit is easy to use. After you follow the instructions in the README, you will be able to download a dataset, run hyperparameter optimization and identify your best-performing multistep prediction models with just three commands: dee... |
May 15, 2023 - PN 4-7
Baier, Alexandra; Aspandi, Decky; Staab, Steffen, 2023, "Supplements for "ReLiNet: Stable and Explainable Multistep Prediction with Recurrent Linear Parameter Varying Networks""", https://doi.org/10.18419/DARUS-3457, DaRUS, V1
This repository contains the necessary scripts to reproduce the results from our paper "ReLiNet: Stable and Explainable Multistep Prediction with Recurrent Linear Parameter Varying Networks". See the README file for more information. The most current version of this software is available on Github. |
May 12, 2023 - EXC IntCDC Research Project 12 'Computational Co-Design Framework for Fibre Composite Building Systems'
Gil Pérez, Marta; Mindermann, Pascal; Zechmeister, Christoph; Forster, David; Guo, Yanan; Hügle, Sebastian; Kannenberg, Fabian; Balangé, Laura; Schwieger, Volker; Middendorf, Peter; Bischoff, Manfred; Menges, Achim; Gresser, Götz Theodor; Knippers, Jan, 2023, "Post-processed and normalized data sets for the data processing, analysis, and evaluation methods for co-design of coreless filament-wound structures", https://doi.org/10.18419/DARUS-3449, DaRUS, V1, UNF:6:3jBvTQjaf+dWmcUwcF1GkA== [fileUNF]
Post-processed and normalized data sets for specimens S2-0, S2-1, S2-2, S2-4, S2-8 and S2-9, used in Figure 14 of the publication: "Data processing, analysis, and evaluation methods for co-design of coreless filament-wound building systems", in the Journal of Computational Design and Engineering. The data allows the comparison of different geometri... |
May 12, 2023 - Materials Design
Forslund, Axel; Jung, Jong Hyun; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals", https://doi.org/10.18419/DARUS-3339, DaRUS, V1
Data for the publication Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals, Phys. Rev. B 107, 174309 (2023). This data set contains - the training sets (VASP files), - the low moment-tensor potentials (MTPs) and high-MTPs, - t... |
May 4, 2023 - Publication: Particulate systems
Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2023, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, and 30% volume rubber content: samples 2 and 3", https://doi.org/10.18419/DARUS-3437, DaRUS, V1, UNF:6:LyvQPm+lMHvJ9Z4neyxihA== [fileUNF]
This dataset contains 12 micro X-ray Computed Tomography (micro-XRCT) data sets from scans of cylindrical particulate mixture samples (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The samples consist of monodisperse stiff (glass) and soft (rubber) particle mixtures. Both particles have an identical diameter of... |
May 4, 2023 - Publication: Particulate systems
Ruf, Matthias; Taghizadeh, Kianoosh; Steeb, Holger, 2023, "micro-XRCT data sets and in situ measured ultrasonic wave propagation of pre-stressed monodisperse rubber and glass particle mixtures with 10%, 20%, 40%, and 60% volume rubber content: sample 1", https://doi.org/10.18419/DARUS-3436, DaRUS, V1, UNF:6:B6SNTx6Co9kvBdKrEWyCwA== [fileUNF]
This dataset contains 8 micro X-ray Computed Tomography (micro-XRCT) data sets from scans of cylindrical particulate mixture samples (diameter 80 mm; unloaded height 80 mm) under different uniaxial compression loads. The samples consist of monodisperse stiff (glass) and soft (rubber) particle mixtures. Both particles have an identical diameter of 4... |
May 3, 2023 - A02: Advanced modelling concepts for coupling free flow with porous-media flow
Gläser, Dennis, 2023, "Dumux Code for flux-mortar method with mpfa", https://doi.org/10.18419/DARUS-3257, DaRUS, V1
This dataset contains the source code for the examples shown in Boon et al. (2022) with the open-source simulator Dumux. The first one investigates the orders of convergence with respect to the mesh size for different element types, as well as the efficiency of the interface preconditioner. The second example simulates a geological case with low pe... |
