Description
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.
| Date made available | 1 Sept 2025 |
|---|---|
| Publisher | TU Delft - 4TU.ResearchData |
Research output
- 3 Article
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Systematic DEM calibration of two-component mixtures using AI-accelerated surrogate models
Hadi, A., Pang, Y. & Schott, D., 2025, In: Powder Technology. 464, 15 p., 121190.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile2 Link opens in a new tab Citations (Scopus)23 Downloads (Pure) -
Adaptive AI-based surrogate modelling via transfer learning for DEM simulation of multi-component segregation
Hadi, A. H., Moradi, M., Pang, Y. & Schott, D. L., 2024, In: Scientific Reports. 14, 1, 20 p., 27003.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile9 Link opens in a new tab Citations (Scopus)18 Downloads (Pure) -
Identification of dominant DEM parameters for multi-component segregation during heap formation, hopper discharge and chute flow
Hadi, A., Shi, H., Pang, Y. & Schott, D., 2024, In: Powder Technology. 444, 22 p., 119985.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile9 Link opens in a new tab Citations (Scopus)51 Downloads (Pure)
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