(732b) Acquiring DEM Validation Data on an Industrial Scale | AIChE

(732b) Acquiring DEM Validation Data on an Industrial Scale

Authors 

LaMarche, C. - Presenter, Particulate Solid Research Inc
Dahl, S. R., University of Colorado at Boulder
Freireich, B., Origin Materials
Cocco, R., Particulate Solid Research, Inc. (PSRI)
Hrenya, C., University of Colorado
Modeling gas-solid flows using discrete element method (DEM) simulations offers promising predictive capabilities for industrial operations. With DEM, Newton’s equations of motion are solved for each particle in the simulation and therefore all collisions are tracked. Furthermore, unlike kinetic-theory-based continuum models, enduring particle-particle contacts can be resolved in DEM such that dense flow of granular material can be simulated. However, the expense of tracking each individual particle frequently prevents the use of DEM simulations at industrial scale. As a result, increasing the computational speed of DEM simulations is an area of active research. An important prerequisite to the reliable use of DEM is validation at the relevant time and length scales. Although DEM hydrodynamic predictions have been compared to numerous small-scale experiments, DEM predictions on an industrially-relevant scale have been prohibitive due to the computational overhead. In this effort, experiments were designed for purposes of DEM validation in an industrially-relevant system. The system considered here is a stripper unit, which involves the co-current flow of solids moving downwards and fluidizing gas moving upwards. The purpose of the stripper unit in an industrial operation is to remove product gases from catalyst particles entrained from a reactor system - e.g., removing the product gases from the interstitial spaces between catalysts. For the purposes of this study, experiments were performed in the industrially-sized system with large, relatively monodisperse particles and conditions controlled in order to limit the number of particles in the experimental section to approximately 109 particles. A detailed explanation of the experimental apparatus will be provided alongside the results. Additionally, the measurements taken to characterize inputs into DEM simulations will be discussed.