Speaker
Description
The discrete element method (DEM) is commonly used to simulate granular flows and optimise processes involving particulate materials in various industries. DEM treats granular materials as individual particles, however the large number of particles present in industrial scales leads to high computational demands, making it less feasible for industrial scale simulations. Coarse graining (CG) presents a potential solution. CG replaces groups of small real particles with larger virtual particles, significantly reducing the number of simulated particles and computational load. However, applying CG to DEM simulations of mixing and segregation processes presents specific challenges, as the goal is to capture the effects associated with the original, fully resolved particle mixture. We investigate the effect of CG on mixing dynamics within a rotating drum across different operational regimes from rolling to cataracting. This approach allows us to observe flows with varying degrees of dynamic behaviour. We evaluate the mixing performance in each drum simulation using different mixing indices. We compare continuous fields, mixing characteristics and features between CG simulations and the original, unscaled simulations across different CG factors and operational regimes.
