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A generalized fluidized bed reactor model across the flow regimes

University of British Columbia

A large number of industrial catalytic and non-catalytic processes employ fluidized beds, and newer and more challenging applications are emerging. Driven by the growth in applications and the challenges they bring, reliable reactor models for fluidized beds are vital for the design, scale-up and optimal operation of these processes. Traditionally, models are often developed with a particular process in mind based on consideration of the operating conditions and flow regime of fluidization, with the range of applicability limited to the cases tested. The complexity is compounded by the existence of distinctly different flow regimes. Considerable uncertainty exists in flow regime transition criteria, and most existing models predict discontinuities at the boundaries, contrary to experimental evidence. In addition, most practically important fluid bed reactors involve complex reactions, sometimes accompanied by significant volume change, with selectivity critical. However, there are few attempts to evaluate reactor model performance using commercial-scale data with selectivity as a criterion. In this research, sponsored by the Mitsubishi Chemical Corporation in Japan, a new generic fluid bed reactor (GFBR) model is developed applicable across the flow regimes most commonly encountered in industrial scale fluid bed reactors: bubbling, turbulent and fast fluidization. The model interpolates between three regime-specific models - the generalized two-phase bubbling bed model, dispersed plug flow, and the generalized core-annulus model - by probabilistic averaging of hydrodynamic and dispersion variables based on the uncertainty in the flow regime transitions. Predictions of hydrodynamic variables across the three fluidization flow regimes are realistic, while conversion predictions are in good agreement with available experimental data. The probabilistic approach leads to improved predictions of reactor performance compared with any of the three separate models for individual flow regimes, while overcoming the difficulties in predicting the transition boundaries among these flow regimes and avoiding discontinuities at these boundaries. Model predictions of selectivities, yields and conversions for two industrial-scale processes (oxidation of naphthalene to phthalic anhydride and oxy-chlorination of ethylene) are reasonable and compare favourably with available plant data. Ability of the model to aid in simulation experimentation over a wide range of conditions is demonstrated. Model predictions are strongly influenced by the reaction kinetics, gas dispersion, superficial gas velocity and reactor temperature. Their accuracy strongly depends on utilizing reliable estimates of the model parameters. Accounting for the volume change due to reaction, caused by a change in the number of moles as well as variations in temperature and pressure along the reactor, improves the performance of the model relative to industrial data. Multiple flow regimes can exist in the same reactor due to changing volumetric flow. The probabilistic modeling approach is shown to effectively track such changes. Application of the GFBR model to gas-solid reactions is demonstrated by coupling a single-particle model with the generic fluid bed reactor model. Predictions from the combined model for the zinc sulfide roasting process are reasonable. However, in order to fully realize the potential of the combined model, some extensions are required. Gas mixing experiments were conducted using both steady state and step change tracer injection in a 4.4 m high and 0.286 m ID column to provide better understanding of the effects of dispersion in each phase, as well as interphase mass transfer, with increasing gas velocities. Data interpretation using a one-dimensional single-phase model and a generalized two-phase model confirmed the expected trends of increasing dispersion in both the low- and high-density phases as the superficial gas velocity is increased. Beyond the transition velocity, U[sub c], however, the dispersion coefficients decreased in some cases. The GFBR model provides a means of predicting hydrodynamics states and quantities in reactors. For given particle properties, operating conditions and reactor geometry, it is possible to predict the flow regime(s) and key hydrodynamic and thermal properties. The model is a useful tool for the design and simulation of fluid bed processes. Further pursuit of the probabilistic modeling approach is well warranted.

Thesis/Dissertation

application/pdf

2009-10-01

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http://hdl.handle.net/2429/13520

Chemical and Biological Engineering

University of British Columbia

UBCV

DSpace