DaRUS (University of Stuttgart)
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Mixed variational formulation and finite-element implementation of second-order poro-elasticity: Datasets
No full textThe datasets provided here are associated with our publication "Mixed variational formulation and finite-element implementation of second-order poro-elasticity". The main idea of the work is to develop a working model for second gradient poro-elasticity. This includes a mixed-variational formulation and finite-element formulation. The results are generated using finite-element software FEAP. The key differences between first-order and second-order models are studied using several boundary value problems. The results for each boundary value problem are provided in HDF files.
Additionally, the results for strain and change in fluid mass content are provided for Terzaghi's consolidation problem and Mandel's consolidation problem applied to layered bodies
Supplemental materials for "Two Empirical Studies on Audiovisual Semiotics of Uncertainty"
No full textWe explored the potential of audiovisual semiotics, the use of audiovisual channels, to enhance users' intuitive perception of uncertainty by conducting two user studies. In the first experiment we assessed the intuitiveness of audio/visual pairs. In the second experiment, we investigated the intuitive audiovisual mappings of uncertainty.
These supplemental materials contain the files for the experimental setup of the two user studies, experimental stimuli used in both experiments, the data collected from the two experiments and r scripts for analysis
Replication Data for: Collision frequencies across collision regimes in two-component systems
No full textThis dataset contains all the solvers and case setups to generate the results used in the paper. More information is available in the README files of the corresponding directories
Replication Data for: Film thickness and gas velocity profile data of the initial measurement campaign of the Falling Film Evaporation Test Rig (FETRIG) at ITLR
No full textThis Dataset consists of the measurement Data of the first measurement campaign of the Falling Film Evaporation Test Rig (FETRIG) at ITLR.
Within this measurement campaign the local film thickness of a falling water film was measured using a confocal chromatic imaging (CCI)-sensor for different liquid Reynolds numbers as well as different gas Reynolds numbers of a counter current gas flow.
For this purpose, a Keyence CL-030P was used with a temporal resoluion of 5000Hz.
Additionall, macroscpoic flow patterns of the falling liquid film were captured with a high speed camera, namely a Krontec Chronos RGB 1.4 utilizing a framerate of 500 fps.
For the investigations of the gas flow, a hot wire anemometer, provided by SVMtec, was used to measure the gas velocity profiles without falling film flow
Simulation Results of the Evaluation of the Stresses Acting on a Thin Shear Driven Water Film
No full textResults of the investigation of instantaneous and time-averaged stresses in a film flow with a thin shear-driven water film below an outer turbulent free flow by using Direct Numerical Simulation (DNS). The film Reynolds number based on the average film velocity and the average film thickness is 50 and the gas Reynolds number based on the average boundary layer thickness and the average gas flow velocity is 54,000
Source code for: generating scattering geometrical imperfections
No full textThis repository contains the python code for the generation of realistically scattering bow and twist imperfections of softwood glulam timber beam-columns. The model was developed in the dissertation of Janusch Töpler
Supplementary material for ''Ring-Expansion Metathesis Polymerization under Confinement"
No full textThis dataset contains simulation input files, topologies and coordinate files in GROMACS format accompanying the mentioned publication. With the provided Jupyter notebooks the data can be visualized and also used for further analysis. We recommend viewing the data by choosing the option "tree"
Video Demonstration of the Combination of Additive and Subtractive Laser Processing for Manufacturing of Small Holes and Narrow Grooves
No full textThis video illustrates a novel approach combining additive and subtractive laser processes at the layer level (AddSub). This quasi-simultaneous manufacturing process enables the fabrication of small structures with high aspect ratios, including narrow grooves below 50 µm in width. The technique demonstrates significant potential for applications in fields such as electric drives and fuel cells, where precision and design freedom are critical
ABxM.DistributedRobotics.RP19: Agent-Based Models for a Modular Collective Robotic Construction System
No full textABxM.DistributedRobotics.RP19 is an add-on to ABxM.Core for agent-based modelling of a collective robotic construction (CRC) system developed in the context of Research Project 19-1 (RP19-1) "Leveraging The Building Material As Part Of The Robotic Kinematic System For Parallel Construction" from the Cluster of Excellence Integrative Computational Design and Construction for Architecture (IntCDC). The add-on contains three agent constructs which revolve around the agent representing the building material or the mobile robots in the modelled CRC system. The agent constructs of BuildingMaterialAgent or MobileRobotAgent are utlized for the sole purpose of architectural design while the agent construct of KCAgent can be used to also robotically plan the structure. The first two constructs are discussed in the paper:
Leder, S., Menges, A. (2023). Introducing Agent-Based Modeling Methods for Designing Architectural Structures with Multiple Mobile Robotic Systems. In: Gengnagel, C., Baverel, O., Betti, G., Popescu, M., Thomsen, M.R., Wurm, J. (eds) Towards Radical Regeneration. DMS 2022. Springer, Cham. (DOI: 10.1007/978-3-031-13249-0_7).
And the other construct is discussed in the paper:
Leder, S., Menges, A.: 2024, Merging architectural design and robotic planning using interactive agent-based modelling for collective robotic construction. Journal of Computational Design and Engineering, Vol. 11, pp. 253-268. (DOI: 10.1093/jcde/qwae028).
The package includes examples files to be to be used within Rhino/Grasshopper that demonstrate implementations of each agent type
Replication Data for: "Local Thermal Non-Equilibrium Models in Porous Media: A Comparative Study of Conduction effects"
No full textThis data set contains the data to reproduce the figures presented in Kostelecky et al., Local Thermal Non-Equilibrium Models in Porous Media: A Comparative Study of Conduction effects, International Journal of Heat and Mass Transfer. \TODO: add doi after acceptance.
1. Final figures
The final figures of the paper can be found in plots_final.tar.xz. It can be extracted e.g in a terminal on Linux via
tar -xf plots_final.tar.xz
2. Generating plot
To generate the plots using the simulation data, download postprocessing_Kostelecky2025a.tar.xz and extract it, e.g. on Linux via
tar -xf postprocessing_Kostelecky2025a.tar.xz
2.1 Structure of folder
The structure of the folder is then as follows:
bin: helper scripts for creating a virtual environment (createAnsActivateVenv.sh) and a master bash script (02_postprocessing.sh) to generate all plots automatically.
02_postprocessing: here, the post-processing is happening via different python scripts. The script process_allDataAndPlotAll.py is calling all other python files for preparing the data (process_PoreResolvedData.py, extract_avgTemperatureInXYZ_forDNM_fromPvd.py and rename_files_REVSimulation.py) and for plotting the prepared data (python scripts are named by plot_....py).
The folder is structured in the subfolders:
00_rawData: here all the simulation data from the different models are stored
01_processedData: when the script process_allDataAndPlotAll.py is called, the simulation data in 00_rawData will be prepared for plotting. Hence, consistent file names and structures are applied as well as mean values are calculated for the dual network model. The prepared data is then stored within this folder.
02_plots: all generated plots will be saved here.
2.2 Run the scripts for generating figures
Generate the plots by executing the script 02_postprocessing.sh:
./02_posptocessing.sh
This opens a virtual python environment, installs the necessary requirements and calls the python script 02_postprocessing/process_allDataAndPlotAll.py, which runs all scripts for preparing and generating the plots automatically. Plots are saved in 02_postprocessing/02_plots.</p