DaRUS (University of Stuttgart)
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Numerical Data for: DNS of water droplet impact onto smooth surfaces at various static contact angles
No full textIn this work, we studied the droplet spreading process and its dependence on the Weber number. We also investigated the influence of the static contact angle on the maximum spreading. This study employs a Computational Fluid Dynamics (CFD) framework to simulate the impact dynamics using the Finite Volume method. The interface is defined by the Volume of Fluid (VOF) method and the Piecewise Linear Interface Calculation (PLIC) method. The Direct Numerical Simulation (DNS) tool Free Surface 3D (FS3D), an in-house code at the Institute of Aerospace Thermodynamics, University of Stuttgart, is utilized.3D simulations are performed for a quarter of the droplet. Six water droplet impact cases are simulated with Weber numbers of 20, 40, 60, 80, 100, and 120. The initial droplet diameter is set to 1 mm, and the corresponding impact velocities are 1.21, 1.71, 2.09, 2.41, 2.70, 2.95 m/s. Each case is studied using static contact angles (CA_st) of 0°, 90°, and 180°. Static contact angles of 0° and 180° were implemented using a solid surface embedded in the computational domain using the cut-cell method introduced in FS3D (see M. Baggio and B. Weigand, “Numerical simulation of a drop impact on a superhydrophobic surface with a wire,” Physics of Fluids 31.11 (2019), 112107). For the case with a static contact angle of 90°, a wall boundary condition is applied at the bottom face of the 3D domain. In the DNS result at the highest Weber number investigated (We = 120) with a superhydrophobic surface (CA_st =180°), the formation of secondary droplets and film breakage was observed. Therefore, no simulation data is provided.
All data for the cases with a static contact angle (CA_st) of 0°, 90° and 180° are provided till 3 ms. Any droplet breakup observed during or after the maximum spreading stage should be considered non-physical. The main goal of this work is to calculate the maximum spreading diameter. The computational domain consists of (512*512*256) cells, which corresponds to 200 cells per initial droplet diameter.The data for all cases are provided in HDF5 format, with filenames as “WeberNumber_StaticContactAngle”. For each timestep, the VOF variable is stored only for the X-Z plane as the spreading is axisymmetric (cropped to 512*1*256 cells). VOF is a scalar field with values between 0 and 1, indicating the phases between ambient gas (air) as 0, and drop liquid (water) as 1, and the interface in between. The results are provided starting from the moment of droplet impact onto the surface.The simulation was performed as part of the GRK 2160 within the subproject SP-B5
Training dataset for AI-supported subject indexing of research data with DFG classification
No full textThis is a structured JSON dataset for training and evaluating AI models for automated subject indexing of research data and linking of research data and publications. It was created for the project DA-FDM in order to train a vector based model to give automated suggestions for the topic classification of research datasets in DaRUS. In the context of this project, the DFG-classification was integrated as a controlled vocabulary in DaRUS for the Topic Classification field. DFG classes were added manually to datasets from DaRUS that were uploaded prior to the integration.
This dataset includes classification tags (DFG, GND, Wikidata), publication links, respective open-access information, and, if the publication is open-access, the respective full texts for datasets from DaRUS as well as TUdatalib.
Example object for the dataset:
{
"name": "doi:10.18419/darus-1234",
"tags": [
{
"name": "dfg-fs$102-04",
"url": "https://w3id.org/dfgfo/2020/102-04"
},
{
"name": "ResearchDataSet"
}
],
"links": [
{
"name": "doi:10.12345/abc5678",
"type": "publication",
"is_open_access": true,
"open_access_url": "https://www.asdfg.com/10.12345/abc5678",
"text": "Extracted publication full text ..."
}
]
}
</p
Supplementary material for "Unlocking Hydrogen’s Potential: Prediction of Adsorption in Metal-Organic Frameworks for Sustainable Energy Storage"
No full textThe data that support the findings of the article "Unlocking Hydrogen’s Potential: Prediction of Adsorption in Metal-Organic Frameworks for Sustainable Energy Storage". The dataset includes all adsorption data obtained from GCMC simulations and from classical DFT calculations ("data") for each investigated porous material. Furthermore, the dataset contains the CIF files of [Zn(bdc)ted]0.5, MOF-5, CuBTC, and ZIF-8. Force field and input files for RASPA-code are given in the folder "raspa_files". All data can be presented in a jupyter notebook.
We recommend viewing the data by choosing the option "Tree"
Additional Data: Mass Transfer Through Vapor-Liquid Interfaces From Hydrodynamic Density Functional Theory
No full textResults from hydrodynamic density functional theory and non-equilibrium molecular dynamics simulations (created with LAMMPS) for the mass transfer through vapor-liquid interfaces. Provided as Python pickle files (.p), which store Python dicts of the density and flux profiles for two temperatures and two mixtures. In addition, a jupyter notebook (.ipynb) for the creation of plots is provided
Synthetic Deep Drawing Dataset
No full textThe dataset comprises 228 deep drawing tools with varying parametric geometries and blank holder forces, resulting in a total of 2280 numerical simulations. The parameter ranges are:
Radius 1: 5–8 mm
Radius 2: 20–55 mm
Height: 25–50 mm
Clearance: 1.1–1.4 mm
Angle: 0–10°
Blank holder force: 15–40 kN
The tools are stored as meshes (step-file) and point clouds (numpy-file). A dataloader is provided
Replication Data for: Flexible Data Mapping in preCICE
No full textThis dataset contains software (preCICE, ASTE, and the heat solver) as well as setup and result files to reproduce the numerical experiments in Chapter 6 of my dissertation titled "Flexible and Efficient Data Mapping for Simulation of Coupled Problems". For further instructions on how to run the experiments see the README.md of the dataset
Visualizations from Efficient Collision-Avoidance Constraints for Ellipsoidal Obstacles in Optimal Control: Application to Path-Following MPC and UAVs
No full textThe provided videos present an experimental validation of a Model Predictive Path-Following Controller (MPPFC) with integrated obstacle avoidance applied to a Crazyflie 2.1 nano quadrotor. The modular, optimization-based control framework incorporates explicit constraints for avoiding collisions between arbitrarily shaped ellipsoids. At the core of the approach is a computationally efficient collision detection condition, which is extended in a novel way to the three-dimensional setting. This enables the quadrotor to follow a given geometric path while dynamically avoiding both static and moving obstacles in real time. In the case of static obstacles, a real-world experiment was conducted. In comparison, for a dynamic obstacle, a simulation-based experiment was performed. A detailed quantitative analysis, as well as further results and details of the experiment, can be found in the related publication associated with these videos
Replication Data for: Lattice distortions and non-sluggish diffusion in BCC refractory high entropy alloys
No full textThe original experiment and simulation data for reproducing the key results in the publication "Lattice distortions and non-sluggish diffusion in BCC refractory high entropy alloys" (Acta Materialia 297 (2025) 121283
Replication Data for: Synthetic and Structural Peculiarities in Molybdenum(VI) Nitrido N-Heterocyclic Carbene Complexes
No full textAll primary data files of measurements and processed data of the journal article mentioned can be found here. This dataset contains the ¹H, ¹⁹F, and ¹³C NMR spectra of all the novel complexes, as well as the single-crystal X-ray structures of selected complexes
Data and code for Reproducibility of GPU-Based Large Eddy Simulations for Mixing in Stirred Tank Reactors
No full textThis dataset contains experimental and numerical results supporting a 30 L stirred-tank mixing-time study conducted at the Institute of Multiphase Flows, Hamburg University of Technology (TUHH). It includes raw and processed measurements from laboratory mixing experiments, M-Star LBM-LES simulations, and complementary Fluent CFD runs.
The data are organized into subdirectories covering experimental probe time series, simulation outputs, post-processing scripts, and final compiled tables and figures used in the associated publication. Together, they enable the reproduction of key analyses on macro-scale flow dynamics, mixing-time evaluation, and grid-resolution sensitivity.
All files are documented with folder-level README files explaining their structure, naming conventions, and relevance to the published results