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Previous simulations of different-sized MTO fluidized beds indicated that the reactive predictions gradually deviate from the experiment with the reactor scale-up. This study aimed to find the underlying reasons by investigating effects of kinetic models and coke content. Two kinetic models were separately integrated into the multi-fluid model, and a reactor model was then established considering coke distribution. It showed that the ratio of ethylene to propylene is still over-predicted even the kinetic model considers the conversion of ethylene to propylene if using average coke content in simulation, but considering a reasonable coke content distribution both models can give better predictions in methanol conversion, hydrocarbon products and selectivity to light olefins. It indicated that coke content distribution plays a critical role in reaction predictions and the kinetic models with similar component classification mainly affect the variation of products along the bed height due to different reaction routes. [Display omitted] • The role of kinetic models are investigated in reactive simulation of an industrial MTO reactor. • The coke content plays a more critical role in reaction predictions. • The kinetic model mainly affects the variation of products along space position in reactor. • Both kinetic models considering coke distribution can give reasonable reaction predictions. [ABSTRACT FROM AUTHOR]

[Display omitted] • A population balance model is proposed for describing the evolution of coke content. • The PBM and multiscale CFD are efficiently combined to simulate an industrial-scale MTO reactor. • The primary light olefins and their selectivity are better predicted. • The relaxation time for expressing the effects of induction period in catalysts are considered. The coke distribution over shape-selective catalysts in fluidized bed reactors is critical to the selectivity of target products. A population balance model (PBM) is developed in this study to describe the evolution of coke distribution due to both reactions and circulation of catalysts. The PBM is coupled with multiscale computational fluid dynamics (CFD) to simulate a methanol-to-olefins fluidized bed reactor. A wide, uneven distribution of coke content can thus be predicted. The mass fractions of the desired products, ethylene and propylene, show better agreement with the experimental data than those without PBM. And the selectivity ratio of ethylene to propylene is also better predicted. Furthermore, the relaxation time of fresh catalyst is considered to express the effects of the induction period in MTO reactions. The reasonable prediction suggests that coupling PBM with multiscale CFD is helpful to understand MTO reactors and may find more application with respect to its optimization and scale-up. [ABSTRACT FROM AUTHOR]

The methanol to olefins (MTO) process opens an economical and important route to produce light olefins. The design of MTO reactor borrows ideas from the reaction–regeneration configuration of the modern fluid catalytic cracking (FCC) units. However, their hydrodynamic behaviors are quite different in the sense that the fluidized bed for MTO reactions operates in different flow regime from that of FCC, calling for new modeling for scale-up. In addition, the coke deposited on catalysts greatly affects the MTO reaction while its generation is very slow. It normally takes tens of minutes or even hours for catalysts to reach the desired level of coke content. Time-dependent computational fluid dynamics (CFD) simulation of such a long process poses a big challenge to reactive multiphase flow modeling. To speed up it, we try to integrate the classic chemical reaction engineering (CRE) model with CFD. In particular, the continuous stirred tank reactor (CSTR) model is established to estimate the steady state distribution of coke content, which is then set as the initial distribution for CFD simulation to shorten the time to reach the steady state of reactive flows. Comparison with experimental data shows good agreement and also great speed-up ratio compared to traditional CFD simulation. [ABSTRACT FROM AUTHOR]