A computational study of the effects of multiphase dynamics in catalytic upgrading of biomass pyrolysis vapor

A recurring challenge among the variety of existing biomass-to-biofuel conversion technologies is the need to ensure optimal and homogeneous contact between the various phases involved. The formulation of robust design rules from an empirical standpoint alone remains difficult due to the wide range of granular flow regimes coexisting within a given reactor. In this work, a volume-filtered Eulerian-Lagrangian framework is employed that solves chemically reacting flows in the presence of catalytic particles. The simulation strategy is used to quantify the role of the particle clustering on catalytic upgrading of biomass pyrolysis vapor in risers. It is shown that particle clustering can reduce the catalytic conversion rate of biomass pyrolysis vapors by up to about 50%. The simulation results are also compared with an engineering model based on continuously stirred tank reactor (CSTR). A one-dimensional Reynolds-averaged transport equation is derived, and the unclosed terms that account for the heterogeneity caused by clusters are evaluated. (c) 2018 American Institute of Chemical Engineers AIChE J, 64: 3341-3353, 2018