In this work, we propose numerical methodologies to combine detailed microkinetic modeling and Eulerian-Lagrangian methods for the multiscale simulation of fluidized bed reactors. In particular, we couple the hydrodynamics description by computational fluid dynamics and the discrete element method (CFD-DEM) with the detailed surface chemistry by means of microkinetic modeling. The governing equations for the gas phase are solved through a segregated approach. The mass and energy balances for each catalytic particle, instead, are integrated adopting both the coupled and the operator-splitting approaches. To reduce the computational burden associated with the microkinetic description of the surface chemistry, in situ adaptive tabulation (ISAT) is employed together with operator-splitting. The catalytic partial oxidation of methane and steam reforming on Rh are presented as a showcase to assess the capability of the methods. An accurate description of the gas and site species is achieved along with up to 4 times speed-up of the simulation, thanks to the combined effect of operator-splitting and ISAT. The proposed approach represents an important step for the first-principles based multiscale analysis of fluidized reactive systems.

PA and ISAT algorithms are developed to speed-up the CFD–DEM simulations of fluidized reactors. Also, a selection procedure of the most effective algorithm according to the operating conditions is developed, enabling the simulation of lab reactors.

This review presents the numerical algorithms and speed-up strategies developed to couple continuum macroscopic simulations and detailed microkinetic models in the context of multiscale approaches to chemical reactions engineering. CFD simulations and hierarchical approaches are discussed both for fixed and fluidized systems. The foundations of the methodologies are reviewed together with specific examples to show the applicability of the methods. These concepts play a pivotal role to enable the first-principles multiscale approach to systems of technological relevance.