251 to 260 of 2,118 Results
Sep 23, 2025 - 2022_ICM_NWG_Greybox_Modelling
Hinze, Christoph; Xu, Haijia, 2025, "Replication Data for: Increasing Dynamic Accuracy using Predictive Feedforward with Hybrid Modeling", https://doi.org/10.18419/DARUS-4513, DaRUS, V1
Experimental dataset for model identification and validation of feedforward control on a five-axis milling machine. This dataset belongs to the Open Access publication "Increasing dynamic accuracy of machine tools using predictive feedforward optimization with hybrid modeling" (doi: 10.1016/j.rcim.2025.103137) A detailed description of the setup ca... |
Sep 16, 2025 - EXC IntCDC Associated Project 42 'Universal Timber Slab'
Alvarez, Martin; Wagner, Hans Jakob; Menges, Achim, 2025, "Slab Building Blocks", https://doi.org/10.18419/DARUS-5096, DaRUS, V1
Overview This dataset defines building blocks for composing floor slabs with a vast range of triangular and rectangular configurations for spans mainly between four and twelve meters. The shapes are generated at regular intervals for different resolutions: 0,1m, 0,2m, and 1.0m. This dataset is meant as a Benchmark Set definition for the project "Un... |
Sep 15, 2025 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media
Hommel, Johannes; Bozkurt, Kerem; Nething, Christoph; Smirnova, Maiia, 2025, "Data used in and produced during calibration and validation of the model for bioconcrete production", https://doi.org/10.18419/DARUS-4814, DaRUS, V1
Data used in and produced during calibration and validation of the model for bioconcrete production in the paper "A numerical 1D reactive flow and transport model for cementation processes in bio-concrete production". Experimental data is derived from Smirnova et al. 2023. The experiment TR1-2 was used to calibrate the developed model for bioconcre... |
Sep 15, 2025 - C04: Pore-scale and REV-scale approaches to biological and chemical pore-space alteration in porous media
Hommel, Johannes; Bozkurt, Kerem; Wang, Yue; Class, Holger, 2025, "Model for Bioconcrete Production", https://doi.org/10.18419/DARUS-4813, DaRUS, V1
This dataset contains the code for the REV-scale model for "A numerical 1D reactive flow and transport model for cementation processes in bio-concrete production". The model was (and can be) applied for various experimental setups, for which input files are provided as well. The setup of these is described in the Readme. Related datasets and reposi... |
Sep 15, 2025 - PN 1-X
Keim, Leon; Weiß, Fiona; Wendel, Kai; Class, Holger, 2025, "Replication Code for: Implementation Pitfalls for Carbonate Mineral Dissolution – a Technical Note", https://doi.org/10.18419/DARUS-4716, DaRUS, V1
This 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... |
Sep 15, 2025 - Data Analytics in Engineering
Scholz, Lena; Ou, Yongliang; Grabowski, Blazej; Fritzen, Felix, 2025, "Supplemental data for "A collapsed interface approach to resolve grain boundaries in finite element simulations of polycrystalline diffusion"", https://doi.org/10.18419/DARUS-5337, DaRUS, V1
This repository contains supplemental data for the article "A collapsed interface approach to resolve grain boundaries in finite element simulations of polycrystalline diffusion" (linked to this dataset; published in Computational Materials Science 260 (2025), article 114172). Further details are provided in the README.md file of this dataset, in o... |
Sep 12, 2025 - PN 1-X
Keim, Leon; Weiß, Fiona; Wendel, Kai; Class, Holger, 2025, "Replication Data for: Implementation Pitfalls for Carbonate Mineral Dissolution – a Technical Note", https://doi.org/10.18419/DARUS-4715, DaRUS, V1, UNF:6:HGhJePghgVQkheBN8H3abw== [fileUNF]
This dataset contains the complete postprocessing workflow for the manuscript "Implementation Pitfalls for Carbonate Mineral Dissolution - a Technical Note". It includes the raw simulation results as CSV files, the Python plotting script for data visualization, and the resulting publication-ready figure. Contents Raw simulation results (CSV files)... |
Sep 12, 2025 - IKT_XTrude
Kattinger, Julian; Hiemer, Stefan; Chung, Phi-Long; Kornely, Mike; Ehrler, Julian; Kreutzbruck, Marc; Bonten, Christian, 2025, "XPTV data set of the flow inside a nozzle of an FFF printer", https://doi.org/10.18419/DARUS-4974, DaRUS, V1, UNF:6:Jl3MgzQnYgdVH3HRx6yqWA== [fileUNF]
This dataset contains raw image data and particle tracking results from X-ray imaging experiments conducted to investigate the flow behavior of molten polymer through a heated nozzle during continuous extrusion, as used in Fused Filament Fabrication (FFF). The data was acquired using 2D projectional radiography inside a μ-CT scanner, with tracer pa... |
Sep 12, 2025 - Quantum Computing @IAAS
Mandl, Alexander; Barzen, Johanna; Bechtold, Marvin; Leymann, Frank; Stiliadou, Lavinia, 2025, "Data repository for "Loss Behavior in Supervised Learning With Entangled States"", https://doi.org/10.18419/DARUS-5174, DaRUS, V1
Replication code and experiment result data for training Parameterized Quantum Circuits (PQCs) with entangled data. The experiments evaluate the structure of the loss landscape during training based on the training sample that is used for training. The combined experiment and data extraction scripts are contained in experiments_and_data_extraction.... |
Sep 11, 2025 - PN 7-6
Kneifl, Jonas; Rettberg, Johannes; Herb, Julius, 2024, "ApHIN - Autoencoder-based port-Hamiltonian Identification Networks (Software Package)", https://doi.org/10.18419/DARUS-4446, DaRUS, V2
Software package for data-driven identification of latent port-Hamiltonian systems. Abstract Conventional physics-based modeling techniques involve high effort, e.g.~time and expert knowledge, while data-driven methods often lack interpretability, structure, and sometimes reliability. To mitigate this, we present a data-driven system identification... |
