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Modeling of gas–solid, heterogeneously catalytic, diameter-transformed fluidized bed (DTFB) reactors is intrinsically complex and requires considering the variation of material properties and operating conditions, because of reactions and/or diameter transformation. The EMMS-matrix drag model, which correlates both operating conditions and local parameters, has been applied in computational fluid dynamics (CFD) simulation of such complex reactors by simplifying the macroscale operating conditions with one set of constant parameters. However, a complete scheme has not been reported that covers a wide range of datasets for a DTFB reactor with complex reactions. To this end, the artificial neural network (ANN), which enables exploring a multivariate relation with the contribution of a set of different parameters, is chosen to couple with EMMS drag modeling. A complete scheme of EMMS-ANN drag for hot, reactive simulation of DTFB is thereby established, with comprehensive evaluation of the contribution of drag markers successively considering the variation of gas properties and operating parameters. Both a priori tests and CFD simulations show that the voidage and slip velocity are the dominant factors in modeling of drag correction, and the effects of dynamic variation of gas properties and operating hydrodynamics are marginal; even the heterogeneous reactions and the change in bed diameter give rise to a remarkable variation in gas properties and operating parameters. The underlying mechanism is then analyzed to provide important clues for drag modeling of gas–solid, heterogeneous catalytic fluidized-bed reactors.

This work investigates the interactions in NOX chemistry during biomass co-combustion in a continuous lab-scale bubbling fluidized bed reactor. Co-combustion experiments were performed at air staged and unstaged conditions, and the gas composition in the flue gas and within the reactor was measured. The used biomass fuels were straw, sunflower husk, sewage sludge, and sunflower seed. Based on the NO concentration in the flue gas, straw-sunflower husk and straw-sunflower seed co-combustion were additive, while co-combustion of straw and sewage sludge revealed a synergy effect. The main cause was the presence of sewage sludge ash, which could catalyse the formation of NO from NH3 and HNCO, and possibly HCN. The catalytic effect of the ash increased with lower ash preparation temperature and better mixing of the ash with straw. During straw-sewage sludge co-combustion, the NH3 initially released from sewage sludge favoured the reduction of NO, while at later stages, when a significant amount of ash accumulated in the bed, the catalytic oxidation of NH3 to NO was dominant. Compared to air unstaged conditions, the NO emission was reduced and the impact of ash on the nitrogen chemistry was less pronounced at air staged conditions.

Gas-solid cyclone separators are widely utilized in many industrial applications and usually involve complex multi-physics of gas-solid flow and heat transfer. In recent years, there has been a progressive interest in the application of computational fluid dynamics (CFD) to understand the gas-solid flow behavior of cyclones and predict their performance. In this paper, a review of the existing CFD studies of cyclone separators, operating in a wide range of solids loadings and at ambient and elevated temperatures, is presented. In the first part, a brief background on the important performance parameters of cyclones, namely pressure drop and separation efficiency, as well as how they are affected by the solids loading and operating temperature, is described. This is followed by a summary of the existing CFD simulation studies of cyclones at ambient temperature, with an emphasis on the high mass loading of particles, and at elevated temperatures. The capabilities as well as the challenges and limitations of the existing CFD approaches in predicting the performance of cyclones operating in such conditions are evaluated. Finally, an outlook on the prospects of CFD simulation of cyclone separators is provided.

The mixing and segregation behaviour of binary solid mixtures has been extensively studied through various experiments, while accurate CFD simulations are difficult to achieve due to process complexity and a lack of reliable constitutive relations. In this study, CFD simulations of a dense fluidized bed with glass and polystyrene particles were performed in order to identify a universal set of simulation parameters and models for simulating binary mixtures with different mixed and segregation behaviour. Through a comparison to experimental data, it was found that the EMMS drag model coupled with the Ma‐Ahmadi solid pressure and radial distribution models predicted more a reasonable axial distribution of solid phases than the Syamlal O´Brien drag model coupled with the Lun et al. solid pressure and radial distribution models. The increase in the solid‐solid drag further improved the simulation results.