| Issue |
Matériaux & Techniques
Volume 114, Number 1, 2026
Special Issue on ‘Advances in Steel Technologies’, edited by Carlo Mapelli, Silvia Barella and Riccardo Carli
|
|
|---|---|---|
| Article Number | 102 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/mattech/2025026 | |
| Published online | 09 February 2026 | |
Original Article
Determining of iron oxide pellet porosity using image analysis and its effect on the reduction behavior
1
Process Metallurgy Research Unit, University of Oulu, PO Box 4300, 90014 University of Oulu, Finland
2
Minerai de Fer Québec / Quebec Iron Ore, 1155 Boul. René-Lévasque O suite #3300, Montreal, QC H3B 3X7, Canada
* email: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
23
September
2025
Accepted:
9
December
2025
Abstract
Hydrogen-based reduction of iron oxide is a promising new technology in fossil-free steelmaking. In the process, the iron oxide is usually fed in a form of spherical pellets or briquettes. In solid-gas-reactions, the porosity of the pellets is assumed to enhance the reduction kinetics via the increase of the available reaction surface area at the reaction interface. However, the multivariable and complex dynamics of the reduction system complicates the estimation of this effect, as it is known that the properties of the pellet evolve withing the progression of the reduction.
In the kinetic analysis procedure, determining the pellet porosity is a demanding task. Measuring the porosity of the pellets is commonly performed using tomography analyses. However, image analysis of X-Ray tomography images of pellet cross-section could provide more practical approach as faster method. In this study, a sophisticated image analysis procedure is developed to analyze the pellets and briquettes porosity based on cross-section images. It was found that the porosity based on image analysis correlates reasonably well with the tomography analysis, with the average percentage error between both approaches being 4.3%. In addition, the effect of cross-sectional porosity on the reduction rate of the pellets is analyzed by making use of kinetic analysis.
Key words: direct reduction / hydrogen / tomography / machine learning
© SCF, 2026
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