Fluidized bed and moving bed reactors are one of the most important technologies in several branches of process industry. Especially, it is known since decades that fine iron ores can be reduced rapidly and efficiently from iron carrier materials using such devices. Within the next decades, most of the carbon-based steel production will be transformed to hydrogen-based technologies. Fluidized beds have the potential to become a key technology for this green steel production. The key advantage in using fluidized beds is that the process step of agglomeration of fine or finest grained iron ores is saved. Nowadays most high-quality iron ores are only available in this form (before agglomeration).
Due to the limited accessibility for measurements, simulation methods have become one of the most important tools for optimizing the iron making processes. While continuum models, such as the two-fluid model [1]or the filtered two-fluid models [2] would be good candidates to attack the simulation of large-scale multi-phase processes it lacks from a proper representation of the particle size distribution and the related physical phenomena. This, in turn, favours particle-based approaches, such as the coupling between CFD and DEM methods, which can easily handle, for example, gas-particle reactions and particle morphology. However, CFD-DEM approaches require considerably large computational resources, since particle-particle collisions have to be resolved. Thus, CFD-DEM is restricted to very small fluidized beds. The situation gets even worse in the case of fine-grained ores.
Following Verma and Padding [3], we implemented a continuum particle model (CPM) into the Opensource code CFDEMcoupling [4]. CPM is a recent approach to multiphase-particle-in-cell (MP-MIC). In contrast to DEM, CPM does not picture individual particle collisions, these are rather modelled by a continuous particle stress tensor. This simplification allows, for example, larger time steps for the particle integration. However, the drawback of CPM is the appropriate definition of the particle stress tensor, which considerably depends on mapping and interpolation schemes. Thus, we introduce a novel face-based mapping/interpolation scheme allowing the determination of a smooth particle stress tensor.
Results show that this new CFD-CPM approach is able to reproduce the fluidization behaviour (i.e. pressure drop, velocity profiles) deduced from reference CFD-DEM simulations but at much lower cost. Finally, CFD-CPM is coupled with a recently proposed reduction model [5] revealing the applicability of this approach for the simulation of the direct reduction of fine-grained ores.

REFERENCES
[1] S. Schneiderbauer et al., Chem Eng Sci, vol. 80, pp. 279–292, 2012.
[2] S. Rauchenzauner and S. Schneiderbauer, Chem Eng Sci, vol. 247, p. 117104, 2022.
[3] V. Verma and J. T. Padding, Chemical Engineering Science: X, vol. 6, p. 100053, 2020.
[4] C. Kloss et al., Progress in Computational Fluid Dynamics, vol. 12, no. 2/3, pp. 140–152, 2012.
[5] M. E. Kinaci et al., Chem Eng Sci, vol. 227, p. 115858, 2020.