Dataset for Magnetic Resonance Imaging Investigation of Hydrodynamic Scale-up in Gyroid Triply Periodic Endo-Skeleton Surface Geometries DOI of this dataset: (https://doi.org/10.15480/882.18011) README file creation date: 30 September 2026 (original) 1. General information: * MRI velocimetry measurement and CFD simulation of Gyroid Triply Periodic Endo-Skeleton Surface (TPnS) structures in DN 40 and DN 100 * Investigation of hydrodynamic scale-up in Gyroid TPnS using MRI velocimetry and cross-validation with CFD simulation * Folder names indicate the method (MRI/CFD) and the nominal reactor diameter (DN 40/DN 100) * Data was collected at Hamburg University of Technology * Muhammad Adrian (muhammad.adrian@tuhh.de, ORCID 0009-0008-3634-9518, Affiliation: a) Institute of Process Imaging, Hamburg University of Technology, Hamburg, Germany, *Corresponding author), Timo Merbach (timo.merbach@tuhh.de, ORCID 0000-0002-7723-5444, Affiliation: b) Institute of Multiphase Flows, Hamburg University of Technology, Hamburg, Germany), Artyom Tsanda (artyom.tsanda@tuhh.de, ORCID 0009-0009-7765-4604, Affiliation: c) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany, d) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany), Christoph Wigger (christoph.wigger@tuhh.de, ORCID 0009-0006-2648-9184, Affiliation: b) Institute of Multiphase Flows, Hamburg University of Technology, Hamburg, Germany), Selma Iraqi Houssaini (selma.iraqi.houssaini@tuhh.de, ORCID 0009-0008-9856-1776, Affiliation: b) Institute of Multiphase Flows, Hamburg University of Technology, Hamburg, Germany), Serhan Acikgöz (serhan.acikgoez@tuhh.de, ORCID 0009-0002-8643-192X, Affiliation: e) Institute for Industrialization of Smart Materials, Hamburg University of Technology, Hamburg, Germany), Dirk Herzog (dirk.herzog@tuhh.de, ORCID 0000-0001-7059-6151, Affiliation: e) Institute for Industrialization of Smart Materials, Hamburg University of Technology, Hamburg, Germany, f) Fraunhofer Research Institution for Additive Manufacturing Technologies, Hamburg, Germany), Felix Kexel (felix.kexel@tuhh.de, ORCID 0000-0003-4268-2348, Affiliation: b) Institute of Multiphase Flows, Hamburg University of Technology, Hamburg, Germany), Stefan Benders (stefan.benders@tuhh.de, ORCID 0000-0002-9823-1928, Affiliation: a) Institute of Process Imaging, Hamburg University of Technology, Hamburg, Germany), Ingomar Kelbassa (ingomar.kelbassa@tuhh.de, ORCID 0009-0003-1325-4472, Affiliation: e) Institute for Industrialization of Smart Materials, Hamburg University of Technology, Hamburg, Germany, f) Fraunhofer Research Institution for Additive Manufacturing Technologies, Hamburg, Germany), Tobias Knopp (tobias.knopp@tuhh.de, ORCID 0000-0002-1589-8517, Affiliation: c) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany, g) Fraunhofer Research Institution for Individualized Medical Technology and Engineering IMTE, Lübeck, Germany), Michael Schlüter (michael.schlueter@tuhh.de, ORCID 0000-0001-5969-2150, Affiliation: b) Institute of Multiphase Flows, Hamburg University of Technology, Hamburg, Germany), Alexander Penn (alexander.penn@tuhh.de, ORCID 0000-0001-5596-6310, Affiliation: a) Institute of Process Imaging, Hamburg University of Technology, Hamburg, Germany) 2. Data overview: * The dataset includes the dataset of the MRI velocimetry measurements, available in .hdf5 files, also including the dataset of the CFD simulation in .raw files * These data can be processed with the script provided in https://collaborating.tuhh.de/v-10/public/manuscripts/tpms-velocimetry * Processed data can be retrieved by executing the scripts * Folder structure: The dataset is organized into folders: MRI/DN40 ├── DN40_ROI_H.hdf5 └── DN40_ROI_pipe.hdf5 MRI/DN100 ├── DN100_ROI_H.hdf5 └── DN100_ROI_pipe.hdf5 CFD ├── DN40 └── DN100 Further details on list of chemical used and additional info are available in Supplementary Information. 3. Variable definitions: n/a 4. Data Collection Methods: The data was generated by measured with a 3 T MRI scanner at the IPI, Hamburg University of Technology. * Liquid medium: An aqueous copper sulfate (CuSO₄) solution was used as the working fluid and circulated vertically upward through the TPnS structures using gear pumps (Gather Industries, Germany and Grundfos, Germany). Over the experimental temperature range (20–22 °C), the fluid density was ρ ≈ 1003.6–1004.1 kg m⁻³. The dynamic viscosity was assumed to be similar to that of water, μ ≈ (0.954–1.0005) × 10⁻³ Pa s. Flow rates were monitored using Coriolis flow meters (Endress & Hauser, Germany) and independently calibrated by timed volumetric collection. The displaced volume over a defined time interval was measured with a graduated cylinder and a stopwatch, which allowed the pump settings to be correlated with the actual flow rates. All analyses were based on time-averaged quantities, so the flow was assumed to be statistically steady. A dedicated degassing system consisting of a vacuum vessel and a vacuum pump (Edwards Vacuum, UK) was incorporated to eliminate trapped air bubbles, which strongly affect MRI phase measurements and flow stability in highly interconnected porous structures. 5. File formats used: * Files are located in measurement-data folders (MRI and CFD dataset) * Files have .hdf5 files for MRI dataset and .raw for CFD dataset 6. Dependencies and Tools: Dependencies are given in the Gitlab repository, where python libraries including versions are declared. 7. Limitations and known issues * Acquisition & Control: scripts depend only on the file type, .hdf5 files for MRI and .raw files for CFD * Format Issues: scripts expect the folder structure and file names described in Section 2. If files are renamed or moved, the file paths in the scripts must be adjusted accordingly * Processing Differences: results may differ slightly if the scripts are run in a different Python environment 8. Usage Rights and Citation: The data is published under CC BY-NC-ND 4.0 license. The dataset can be cited by the DOI provided by TORE. By using the data in your work, you agree to cite the original work.