438210 Modeling the Impact of Bubbling Bed Hydrodynamic Oscillations on the Yield of Biomass Fast Pyrolysis Oil

Sunday, November 8, 2015
Exhibit Hall 1 (Salt Palace Convention Center)
Qingang Xiong, Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN

Modeling the impact of bubbling bed hydrodynamic oscillations on the yield of biomass fast pyrolysis oil

Qingang Xiong

Oak Ridge National Laboratory, Oak Ridge, Tennessee

Email: xiongq@ornl.gov

Abstract Fast pyrolysis of biomass, in combination with catalytic upgrading of the resulting oils, has become a leading candidate technology for producing renewable transportation fuels and high-value organic chemicals from biomass. Bubbling fluidized bed reactors are widely used for biomass pyrolysis because of their excellent heat and mass transfer, but their complex nonlinear dynamics pose a significant challenge to achieving the needed degree of chemical reaction control. As a part of our participation in DOE’s Computational Pyrolysis Consortium (www.cpcbiomass.org), we are conducting numerical simulations of a laboratory-scale bubbling fluidized-bed pyrolysis reactor to investigate the effects of bubbling bed hydrodynamics on the temporal variations in bio-oil yield and composition. The yield and composition of the raw pyrolysis oil is critical to the success of further upgrading steps, such as vapor-phase or liquid-phase deoxygenation and hydrogenation. In the simulated pyrolysis reactor, all phases were modeled as interpenetrating continua through the so-called multi-fluid model within the framework of the open-source code MFIX. A global multi-component multi-step mechanism proposed in the literature for biomass was chosen for simulating the fast pyrolysis reactions. The instantaneous product yields over time were predicted at the reactor exit and their overall statistics characterized. The initial bed height, fluidization intensity, and biomass injection rate were changed to shift the hydrodynamic state in order to observe the resulting temporal and statistical variations in the product yield and composition. Based on these results, we recommend general limits on the operating conditions for biomass bubbling bed pyrolyzers and suggest specific directions for future experimental and computational studies of biomass fast pyrolysis.

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