(174c) Advantages and Drawbacks of Coarse-Grained CFD-DEM and Eulerian Multiphase Simulation for Plant-Scale Fluidized Beds

Since its introduction [1], the Discrete Element Method (DEM) has proven to be a valuable method for the analyzing and understanding particulate flows. Supported by the continuously increasing computational power, CFD-DEM simulations have found their way into the chemical and process industry for various applications like solid suspension in mixing vessels, fluidized and spouted beds, granular transport and coating applications in rotary drums [2,3].

The major shortcoming of DEM, however, is its computational cost that increases with the amount of particles involved, their material properties (stiffness) and size. This hinders the application of CFD-DEM simulation to large-scale systems of industrial size. To overcome this shortcoming a coarse grain (CG) model has been described [4]. Using straightforward scaling rules, a group of particles gets replaced by a representative coarse parcel. This effectively reduces the number of particles that need to be processed and subsequently shortens the computational time. On the other hand they introduce a modeling error into the simulation. In a previous study we were investigating different coarse graining models and quantify the effect on different parameters and their fluctuation like pressure drop and expansion height in a fluidized and spouted bed and we were comparing the simulation with experimental results. In general it can be stated that bed expansion and pressure drop are well predicted for all investigated CG methods, but depending on the CG factor the dynamic of the system cannot be captured. [NEU]

In this work we are comparing these CFD-DEM results with simulation results from a particle unresolved simulation based on the Kinetic Theory of Granular Flow (KTGF). In this modeling framework the different phases are treated as interpenetrating continua (Eulerian Multiphase), but additionally the intraphase interaction of the dispersed solid phase is considered. A validation of different KTGF-models and the influencing model parameters is discussed in lab-scale and results for industrial scale are shown. Additionally the KTGF results are compared against the DEM results w.r.t. computational cost and accuracy.

References:

1. A. Cundall, O.D.L. Strack, Geotechnique, 29 (1979), 47
2. Eppinger, O. Baran, R. Aglave, S. Lo, Simulating Solid Suspension in Stirred Vessels with a Fully Coupled CFD-DEM Algorithm (161d), AIChE Annual Meeting 2017, Minneapolis
3. Baran, R. Aglave, M. Tandon, A. Karnik, S. Lo, Numerical Simulation of Dense Gas-Solid Fluidized Beds: Comparison Between Eulerian Multiphase and Discrete Element Methods, AIChE Annual Meeting 2015, Salt Lake City, UT.
4. Sakai, Y. Yamada, Y. Shigeto, K. Shibata, V.M. Kawasaki, S. Koshizuka, Numerical Methods in Fluids 64 (2010), 1319
5. Eppinger, T., Tourani, C., Aglave, R., Quantifying Effects of Coarse-Grain Model Parameter in CFD-DEM Simulations of Fluidized and Spouted Beds and Comparison Against Eulerian Multiphase Simulation Results, AIChE Spring Meeting 2019, New Orleans