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UBC Theses and Dissertations

Heat and mass transfer in pulsed fluidized bed of biomass Jia, Dening


Biomass is a promising energy source that has been considered in a variety of thermal conversion processes where fluidized beds with their exceptional heat and mass transfer rates, are often considered as potential candidates. However, the fluidization of biomass is held back by its cohesive nature. This work has demonstrated that pulsed gas flow in fluidized bed is highly effective in overcoming channeling, partial and complete defluidization, without the need for inert bed particles. Both heat transfer and mass transfer were investigated in a pulsed fluidized bed with 0.15 m by 0.10 m rectangular cross-section area, and a fluidized bed with a tapered bottom to improve reactor performance. Biomass used in this work included Douglas fir, pine and switchgrass. Batch drying test was selected as an indirect indicator of gas–solid contact, heat and mass transfer. Mass transfer was evaluated through batch drying tests, where better gas–solid contact and mass transfer was assessed through the water removal efficiency. An optimum operating condition was identified after analyzing the intricate relationship between pulsation frequency, gas flow rate and the hydrodynamics. A two-phase drying model that linked single-particle mass transfer to macroscopic hydrodynamics in fluidized bed was implemented to verify the effect of flow rate, temperature and biomass properties on drying and mass transfer. Good agreement was observed between the modelled effective diffusivity and experimental results. Bed-to-surface heat transfer coefficients of all three biomass species in two reactor geometries were measured at various operating conditions. The heat transfer coefficient was influenced greatly by the intensity and frequency of gas pulsation, where both particle convection and gas convection existed. A new heat transfer model was proposed to address the influence of gas pulsation. Modelling results showed good agreement with experimental data.

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