DaRUS (University of Stuttgart)
Not a member yet
2037 research outputs found
Sort by
DuMuX code for modelling evaporation-driven density instabilities in unsaturated porous media
No full textThis dataset contains the source code to reproduce the numerical simulations presented in Bringedal et al. Impact of saturation on evaporation-driven density instabilities in porous media: mathematical and numerical analysis, Transport in Porous Media, https://doi.org/10.1007/s11242-025-02207-y.
The application allows to model the estimated onset and the development of evaporation-driven density instabilities in an unsaturated porous media. Therefore, a simplified Richards equation is solved. </p
Supplementary material for 'Probing Self-Diffusion of Guest Molecules in a Covalent Organic Framework: Simulation and Experiment'
No full textThis dataset contains input files and results from Grand Canonical Monte Carlo (GCMC) adsorption simulation and Molecular Dynamics (MD) Simulation.
All data is presented in a jupyter notebook and for a fast overview without executing the notebook also as PDF-file.
Furthermore the dataset contains the modified cif files of COF PI-3, including partial charges obtained with DDEC method (input_files/frameworks). Force field and input files for the RASPA and GROMACS codes are available in data/input_files/.
We recommend viewing the data by choosing the option "Tree"
The Categorical Data Map - Replication Data
No full textSource code and datasets used for our experiments are shared for replication purposes along our publication "The Categorical Data Map". We describe each of the six datasets individually on a per-file basis. All datasets are purely nominal datasets
Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material
No full textWe evaluated several animations for transitions between scatter plots in a crowd-sourcing study. We published the results in a paper and provide additional information within this supplemental material.
Contents:
Tables that did not fit into the original paper, due to page limits.
An anonymized print-out of the preregistration.
The original preregistration is available at OSF (DOI) and on the internet archive.
Videos demonstrating the tasks used in the study:
used to record samples for the study,
used for participant training,
and used to detect distracted participants and bots.
An interactive demonstration of all study tasks (including training and attention checks).
The source code is contained within the directory ./interactive-demo/ of this supplemental material and also available at GitHub.
The animation library that we used for the study. We also include a test page for readers to use with their own data sets.
The source code is contained within the directory ./animation-library/ of this supplemental material and also avialable at GitHub.
The list of nonsensical statements that we used for attention checks on Prolific.
The statistical tests with the recorded study data, some of which we reported in the main paper. We also provide reports from the preliminary power analysis that we performed to determine the number of participants for the study.
The recorded pseudo-anonymized study data for further analysis.
</ul
exaFOAM Industrial Benchmark B2 - Unsteady primal and adjoint solution around the TME CHR car
No full textThis work is part of the exaFOAM project that aims to enable the open-source CFD software OpenFOAM to exploit massively parallel HPC architectures and overcome performance scaling bottlenecks. This benchmark represents an industrial application of the unsteady optimization infrastructure of OpenFOAM, using the Toyota CHR car geometry. When used with unsteady flows, the adjoint equations are integrated backwards in time, requiring the instantaneous flow fields to be available at each time-step of the adjoint solver, which noticeably increases storage requirements in large-scale problems. To avoid extreme treatments, such as the full storage of the computed flow fields or their recomputations from scratch during the solution of the adjoint equations and to reduce the re-evaluation overhead incurred by the widely used check-pointing technique, lossy compression techniques were implemented into the adjointOptimisation library of OpenFOAM, during the exaFOAM project. The re-computation cost is reduced by efficiently compressing the entire compressed flow series and storing it in memory. The current data-set includes the CFD mesh and a snapshot of the DDES flow solution (restart files), obtained after discarding 1 second of the transient part. Detailed information and case setup can be found in the README.md file contained in the case setup file
SynDAB Dataset
No full textThe dataset comprises a collection of images captured from the perspective of an excavator. The images depict a landfill with various environmental contexts. Specifically, various type of barrels are contained. Moreover, the dataset contains the simulated LiDAR data of these scenes
Harvester-Curator, a tool to elevate metadata provision in data and/or software repositories
No full textHarvester-Curator is a tool, designed to elevate metadata provision in data repositories. In the first phase, Harvester-Curator acts as a scanner, navigating through user code and/or data repositories to identify suitable parsers for different file types. It collects metadata from each of the files by applying corresponding parsers and then compiles this information into a structured JSON file, providing researchers with a seamless and automated solution for metadata collection. Moving to the second phase, Harvester-Curator transforms into a curator, leveraging the harvested metadata to populate metadata fields in a target repository. By automating this process, it not only relieves researchers of the manual burden but also ensures the accuracy and comprehensiveness of the metadata. Beyond its role in streamlining the intricate task of metadata collection, this tool contributes to the broader objective of elevating data accessibility and interoperability within repositories
D1244 sensor data (December 2023)
No full text
General information:
This dataset contains measurements from the adaptive high-rise demonstrator building D1244, built in the scope of the CRC1244. This 36m high building is equipped with 24 hydraulic actuators providing the basis for its structural adaptation. Strain gauges, pressure sensors and position encoders are mounted throughout the building and used for state estimation and monitoring.
Structure of the dataset:
Each zip-file contains measurements of one day in the hdf5 format.
The hdf5-files in each zip-file contain an array of 244 signals sampled over 10^6 time steps at approximately 200Hz.
labels.csv contains auxiliary information on all measured signals, including the sensor type and the sensor's location in the building
File contents:
Each hdf5-file contains signals of the following types, arranged as stated in labels.csv:
strain: strain (in mm/m) in columns and diagonal bracing elements, measured by strain gauges.
pressure: pressure (in bar) in the piston side or the rod side chamber of a hydraulic actuator. For actuators in the diagonal bracing, the rod side chamber is permanently connected to the tank.
posenc: displacement (in meters) of each actuator, measured by a position encoder.
optic: optically measured displacement (in meters) of emitters attached to the building's facade.
The building consists of four modules spanning three stories each, and all sensors within a module are connected to a control cabinet, from which all measurements are transmitted. The cameras of the optical measurement system are placed outside the building and transmit their data separately from the sensors within the building. Therefore, there are an additional two signals per module (or camera):
timestamp: unix timestamp (seconds since 1st January 1970) of the control cabinet
numvars: number of measured variables
Missing measurements are marked as NaN. The optical measurement system is currently undergoing maintenance, which is why the corresponding signals are all NaN.
</p
Replication Data for: Transferable Anisotropic Mie Potential Force Field for Alkanediols
No full textSupplementary material is provided for the Transferable Anisotropic Mie Potential Force Field for Alkanediols, including files for rerunning TURBOMOLE DFT calculations for 1,2-ethanediol and 1,3-propanediol. The dataset includes input files and results for the OCCO and OCCC torsion with various constrained H positions. Moreover, numerical values for transport and vapor-liquid equilibrium data are provided
Raw audio samples of the CNVVE dataset
No full textThis CNVVE Dataset contains raw audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or
“mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective folders. The
samples are recorded through a dedicated website for data collection that defines the purpose and type of voice data by providing example recordings to
participants as well as the expressions’ written equivalent, e.g., “Uh-huh”. Audio recordings were automatically saved in the .wav format and kept
anonymous, with a sampling rate of 48 kHz and a bit depth of 32 bits.
This dataset contains a raw version of the samples. A cleaned version of these samples can be found on https://doi.org/10.18419/darus-3898.
For more info, please check the paper or feel free to contact the authors for any inquiries.</p