The Multi-Level Coarse-Grain Model used in CFD-DEM Simulations of Iron Ore Reduction
Sprache des Vortragstitels:
9th World Congress on Particle Technology
Sprache des Tagungstitel:
Applying the discrete element method (DEM) or CFD-DEM simulations to large-scale industrial systems such as blast furnaces or direct reduction shaft furnaces quickly reveals the limits of this simulation strategy. To reduce the computational cost it is inevitable to decrease the level of detail of the method. A potential candidate is the coarse-grain (CG) approach to the DEM (Bierwisch et al., 2009) which lowers the computational demand by using coarser (pseudo) particles to represent a certain amount of original particles. However, due to the violation of geometric similarity, this simple coarse-graining approach fails to capture effects that inherently depend on particle size.
Recently, a multi-level coarse-grain (MLCG) model of the DEM (Queteschiner et al., 2018) has been proposed to alleviate the deficiencies and increase the applicability of DEM coarse-graining. In this model multiple concurrently simulated coarse-grain levels are coupled to adjust the resolution of the system as needed. The MLCG model can also be applied to fluid-particle systems using CFD-DEM. To fully picture industrial plants involving the reduction of iron ore, however, the ability to consider heat transfer and chemical processes is also indispensable. In this work, the reduction process encountered is described via a three-layer unreacted shrinking core model (Valipour, 2009) considering the different iron oxides hematite, magnetite and wüstite as well as the surrounding gas properties. For the MLCG model this means that additional information needs to be transferred between the differently resolved DEM CG-levels as well as between the DEM and the CFD components, i.e. particle temperature and reduction state. In this study we have verified this additional functionality using a silo filled with iron ore pellets undergoing reduction at elevated temperatures.