Data underlying the PhD thesis "Mixtures in Motion: High-Velocity DEM Modeling of Blast Furnace Charging"

DOI:10.4121/7e149c70-ad49-4ea1-88c6-8a7c2d494a9f.v1
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DOI: 10.4121/7e149c70-ad49-4ea1-88c6-8a7c2d494a9f

Datacite citation style

Roeplal, Raïsa (2025): Data underlying the PhD thesis "Mixtures in Motion: High-Velocity DEM Modeling of Blast Furnace Charging". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/7e149c70-ad49-4ea1-88c6-8a7c2d494a9f.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset contains numerical and experimental data generated in the context of my PhD research on particle-scale flow and packing behavior in high-velocity blast furnace mixture charging, where the mixture consists of granular iron ore pellets and sinter. The work combines computational research, using Discrete Element Method (DEM) simulations, and laboratory experiments for model calibration and validation. The numerical data comprise DEM simulation outputs used to analyze flow, segregation, and packing behavior under blast-furnace-relevant conditions (corresponding to Chapters 4, 7 and 8 of the PhD thesis). The experimental data originate from high-velocity piling tests designed to calibrate DEM model parameters (Chapters 5 and 6), and include measurements of hopper discharge and subsequent heap formation characteristics for pellets, sinter, and their mixture. Together, these data support the development, calibration, and assessment of a DEM model for industrial-scale charging applications.

History

  • 2025-11-05 first online, published, posted

Publisher

4TU.ResearchData

Format

data/.txt, data/.xlsx

Funding

  • Industrial Dense Granular Flows Project (grant code 741.019.202) NWO

Organizations

TU Delft, Faculty of Mechanical, Engineering, Department of Maritime and Transport Technology, Transport Engineering and Logistics

DATA

Files (9)