The Multi-Level Coarse-Grain Model used in CFD-DEM Simulations Involving Heat Transfer and Chemical Reactions
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
VII International Conference on Particle-Based Methods (PARTICLES 2021)
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Using the discrete element method (DEM) or CFD-DEM simulations for the investigation of large-scale industrial systems such as blast furnaces or direct reduction shaft furnaces easily exceeds the limits of feasibility. Hence, it is necessary to introduce certain model simplifications. An eligible candidate is the coarse-grain (CG) model of the DEM which lowers the computational demand by using coarser (pseudo) particles to represent a certain number of original particles. However, due to the violation of geometric similarity, this simple coarse-graining approach fails to capture effects that intrinsically depend on particle size.
We have previously introduced the multi-level coarse-grain (MLCG) model of the DEM to alleviate the deficiencies and increase the applicability of DEM coarse-graining. In this model we concurrently couple multiple coarse-grain levels to adjust the resolution of the simulation as required.
The MLCG model can also be applied to fluid-particle systems using CFD-DEM. To fully picture industrial plants, however, the ability to consider heat transfer and chemical processes, e.g. the direct reduction of iron ore, was missing. Additional information transfer between the differently resolved DEM levels as well as between the DEM and the CFD components are required for this task. In the
latest iteration of the MLCG model we have added and validated these missing capabilities.
The new functionality is demonstrated via a simulation of a small-scale silo filled with iron ore pellets undergoing direct reduction at elevated temperature. Temperature evolution and the progress of the reduction process were compared to a fully resolved reference simulation of the system. Good agreement was found for both representations of the system.