DaRUS (University of Stuttgart)
Not a member yet
2037 research outputs found
Sort by
Depth progress of ultrafast laser drilling measured by means of X-ray synchrotron imaging
No full textThis dataset contains sets of video frames taken from synchrotron x-ray videos of laser drilling with an ultrafast laser in 1.4301 stainless steel. The x-ray videos show the crossectional distribution of material density and thickness in the plane of the borehole axis.
Each set is packaged in a multipage tiff file and contains selected video frames of a single laser drilling process. The video frames are taken from the video at a progress of the drilling depth of about every 50 µm.
The vertical size of the yellow rectangle in each video frame represents the manually determined drilling depth 'z_tip'. A detailed description can be found in the related publication. The dataset also includes a complementary set of tables (csv files). In each table a column contains corresponding the time stamps to each video frame in seconds and the drilling depth in µm.
The relation between frame number and timestamp, and the relation between the size of the yellow rectanngle and the depth in Micrometer is described in the diagram pdf file
CSI Dataset espargos-0005: Four phase- and time-synchronous ESPARGOS antenna arrays in a lab room
No full textDataset containing WiFi channel state information (CSI) alongside ground truth data (position tags, timestamps) measured with ESPARGOS antenna arrays. Measurement parameters and machine-readable file format descriptions are provided in a JSON file (spec.json).
Four ESPARGOS arrays are placed in the corners of a lab room. Even though they are distributed in space, they are synchronized in both time and phase thanks to wired clock / phase distribution
Matlab Code and Data for: Data-driven geometric parameter optimization for PD-GMRES
No full textThis repository contains the Matlab code and generated data for the manuscript "Data-driven geometric parameter optimization for PD-GMRES" which uses a quadtree approach to optimize parameters for the iterative solver PD-GMRES. It includes hardware specific data to allow for reproducibity of our results. Our calculations were performed using MATLAB R2019a and should be reproducible up to and including version R2022a. A change in version R2022b leads to different numerical behavior. However, the code does run on newer Matlab versions. Further information is contained in the README
Data for: Intermittent flow paths in biofilms grown in a microfluidic channel
No full textContent:
This dataset includes images of 10 different biofilm growth experiments to observe intermittent flow paths in a microfluidic channel. All images taken by optical microscopy per five minutes. The experiments took in avarage 4-5 days. The published data is the raw images of the experiments. The images names were related to the timestamps as [YYYY_MM_DD_hh-mm-ss].
All further referenced files are compressed into the folder Files.tar.gz. After extracting, all files are accessible.
This dataset contains in detail:
The captured images of the experiments used for post processing to evaluate the frequency of the intermittent flow paths.
E2_images.tar.gz contains the images of the experiment with an average starting nutrient broth velocity of 0,23 mm/s in the narrow channel.
E3_1_images.tar.gz contains the images of the first experiment with an average starting nutrient broth velocity of 0,8 mm/s in the narrow channel.
E3_2_images.tar.gz contains the images of the second experiment with an average starting nutrient broth velocity of 0,8 mm/s in the narrow channel.
E4_1_images.tar.gz contains the images of the first experiment with an average starting nutrient broth velocity of 1,6 mm/s in the narrow channel.
E4_2_images.tar.gz contains the images of the second experiment with an average starting nutrient broth velocity of 1,6 mm/s in the narrow channel.
E5_images.tar.gz contains the images of the experiment with an average starting nutrient broth velocity of 0,8 mm/s in the wide channel.
The captured images used to qualify the biofilm growth and the occurrence of intermitting flow paths with higher and lower velocities compared to the experiments where intermittency was clearly visible.
E1_images.tar.gz contains the images of the experiment with an average starting nutrient broth velocity of 0,114 mm/s in the narrow channel.
E1.2_images.tar.gz contains the images of the experiment with an average starting nutrient broth velocity of 0,114 mm/s in the narrow (repetititon).
E1.3_images.tar.gz contains the images of the experiment with an average starting nutrient broth velocity of 0,114 mm/s with higher nutrient concentration in the narrow channel.
E6_1images.tar.gz contains the images of the first experiment with an average starting nutrient broth velocity of 1,6 mm/s in the wide channel.
E6_2_images.tar.gz contains the images of the second experiment with an average starting nutrient broth velocity of 1,6 mm/s in the wide channel.
E7_images.tar.gz contains the images of the experiment with an average starting nutrient broth velocity of 0,8 mm/s in narrow channel with pore bodies.
</ol
Replication Code for: Implementation Pitfalls for Carbonate Mineral Dissolution – a Technical Note
No full textThis dataset contains a Docker image that provides a complete computational environment for reproducing the numerical calculations presented in our manuscript. The image includes pre-built installations of DuMuX and Reaktoro, configured to run our specific simulation cases.
Contents
docker_image_paper_reviewer.tar (8.8 GB): Docker image containing the full computational environment
Running Simulations and Data Transfer
Create and prepare the output directory:
mkdir output
chmod 777 output
Load the image into Docker:
docker load
Run the container with mounted output directory:
docker run -itv ./output:/home/reviewer/output reviewer_docker_new
To detach from the container without stopping it:
Press Ctrl+P followed by Ctrl+Q
To reenter a detached container:
docker ps
Find your container ID, then:
docker attach CONTAINER_ID
Inside the container, run the DuMuX simulation:
cd {REAKTORO_BATCH_DIR}/build
./calcite_dissolution_corrected
./calcite_dissolution_palandri_kharaka
Copy results to the mounted output directory:
cd {OUTPUT_DIR}/
cd {OUTPUT_DIR}/
cp reaktoro-corrected.csv ${OUTPUT_DIR}/
Exit the container:
Type exit or press Ctrl+D
The results are now available in your local './output' directory
Security Notice
This Docker container requires elevated privileges to run. While we ensure no malicious content is included, as with any third-party software requiring elevated privileges, users should exercise appropriate caution. For maximum security, users can alternatively build the environment themselves using our publicly available Dockerfile and installation instructions at: Git Repository
Alternative Installation
For users who prefer to build the environment manually or cannot use the provided Docker image, please refer to our Git Repository which contains:
Source Code of Simulations
Complete Dockerfile
Manual installation instructions
All necessary source code and configuration files
</ul
Replication Data for: "Lubricant Temperature Observer for Gearboxes in Industrial Robots"
No full textThe dataset provides the temperature measurements used for identification and validation in the publication "Lubricant Temperature Observer for Gearboxes in Industrial Robots".
It was recorded with the presented experimental setup, which represents an industrial robot joint consisting of motor and gearbox and is equipped with three temperature sensors.
These sensors measure lubricant, housing and environment temperature.
The dataset is divided into two folders: "identification" and "validation".
The folder "validation" contains subfolders for the three validation scenarios described in the paper: heat-up, long-term and cool-down.
Each file contains one measurement with the desired motor velocity theta_dot in rad/s given in the file name.
The measurement data is structured in five columns: time t in s, lubricant temperature T_L in °C, housing temperature T_H in °C, environment temperature T_E in °C, motor velocity theta_dot in rad/s and friction torque tau_f in N m.
The MATLAB function "read_data.m" can be used to import the dataset into a MATLAB structure array.
It is used in the MATLAB script "plot_figures.m" to plot the temperature measurements
Trained Models on Synthetic Permeability Fields, 3+1 Data Points
No full textModels are trained with Heat Plume Prediction.
Steps 1 and 3 of LGCNN (Local Global Convolutional Neural Network) are separate, step 2 is a numerical solver that does not require any trained model.
The vanilla UNet can be applied directly end-to-end, just does not give very good results.
For inference follow the guidelines of Heat Plume Prediction and applied all 3 steps/models sequentially to your input data.
Based on raw data from https://doi.org/10.18419/darus-5063
Data for: "The extent of the Rhine Glacier in eastern Upper Swabia (southern Germany) at the height of the Last Glacial Maximum: new morphological constraints from high-resolution digital terrain models"
No full textHigh-resolution LiDAR data of Upper Swabia.
The files in the dataset represent the figures of the related publication in high resolution.</p
QoI - Droplets
No full text
This dataset consists of a database of regular and distorted droplets with droplet clusters extracted from high-resolution shadowgraphy images in technical sprays. It serves as a subclass for generating synthetic training data via domain randomisation, which is subsequently used to train Deep Learning (DL) based image segmentation models.
A more detailed description is provided in the corresponding paper:
https://doi.org/10.1016/j.ijmultiphaseflow.2023.104702
Data Samples
Regular droplets:
Distorted droplets:
</p
Replication Data for: Modeling Quantum Volume Using Randomized Benchmarking of Room-Temperature NV Center Quantum Registers
No full textCSV datasets required to reproduce all plots in the main paper are provided. Details on how the data were acquired and their interpretation are described in the corresponding manuscript