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DOI: 10.4121/aca78cf8-0ffc-4827-9481-3dd4a9930257

Hadi, Ahmed; Schott, Dingena; Pang, Yusong (2025): Data and codes for DEM modelling and calibration of multi-component segregation. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/aca78cf8-0ffc-4827-9481-3dd4a9930257.v1

Categories

• Mechanical Engineering
• Engineering

Keywords

Calibration Discrete element model (DEM) machine learning Sensitivity analysis Surrogate modelling

Licence

CC BY 4.0

Interoperability

• RO-Crate Metadata

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by Ahmed Hadi , Dingena Schott , Yusong Pang

This dataset contains the data and codes underlying the PhD thesis of Ahmed Hadi (TU Delft), which focuses on Discrete Element Method (DEM) modelling and calibration of multi-component segregation in blast furnace charging systems. It includes reference DEM simulation decks (Altair EDEM), statistical analysis files from Definitive Screening Design (JMP Pro), input–output datasets for machine learning, Matlab codes for surrogate modelling and optimisation, and calibration reference decks. The dataset is organised by thesis chapter and linked to published journal articles. It enables researchers to reproduce the simulations, apply the machine learning models, and extend calibration studies of granular segregation in industrial-scale systems.

History

• 2025-09-01 first online, published, posted

Publisher

4TU.ResearchData

Format

.edem .jmp .xlsx .m .txt

Associated peer-reviewed publication

Identification of dominant DEM parameters for multi-component segregation during heap formation, hopper discharge and chute flow

References

• https://doi.org/10.1038/s41598-024-78455-7
• https://doi.org/10.1016/j.powtec.2025.121190

Organizations

TU Delft, Faculty of Mechanical Engineering, Department of Maritime and Transportation Technology