Cluster level analysis of mass transfer in a riser using CFD-DEM

Abstract

Particle clustering is prominent in risers, reducing gas-solid contact. This work numerically examines mass transfer between gas and clusters in fully developed region of a riser. To this end, particle clustering with a first-order catalytic bio-oil upgradation reaction in a triply periodic domain is simulated using four-way coupled CFD-DEM, an Eulerian-Lagrangian approach. Two mass transfer mechanisms in particle clusters are investigated: cluster breakup and gas velocity fluctuations within clusters. This analysis is performed by accessing individual cluster-level information using our recently developed technique based on DBSCAN : Density Based Spatial Clustering of Applications with Noise, an unsupervised ML algorithm. We show that the commonly used particle response time underpredicts the mass transfer timescale, whereas cluster breakup overpredicts the mass transfer timescale and is independent of the cluster size. In contrast, gas velocity fluctuations within clusters accurately predict mass transfer in particle clusters. Moreover, the mass transfer timescale based on the gas velocity fluctuations increases linearly with the cluster size.