(529c) Numerical Investigation of Multiphase Dynamic Effects in Catalytic Upgrading of Biomass Pyrolysis Vapor

Authors: 
Capecelatro, J. S., University of Michigan
Pepiot, P., Cornell University
Desjardins, O., Cornell University
Jarvis, M., National Renewable Energy Laboratory
Foust, T. D., National Renewable Energy Laboratory



A
recurring challenge among the variety of existing biomass-to-biofuel conversion
technologies is the need to ensure optimal and homogeneous contact between the
various phases involved. One example can be found in the catalytic upgrading of
bio-oil vapors, a bi-phasic process critical in pyrolysis-based conversion, typically
performed in circulating fluidized bed (CFB) reactors. While the upgrading
process is expected to strongly depend on the contact time between raw gas and
catalysts, and on catalysts deactivation over time, the formulation of robust
design rules from an empirical standpoint alone remains difficult, due to the wide
range of granular flow regimes coexisting within the reactor, from near close-packing
at the bottom of the reactor to more dilute conditions in the riser. The issue
is amplified by the highly unsteady and turbulent nature of gas-solid flows. In
particular, clusters of particles are known to form in risers, which can significantly
decrease the overall catalytic activity in the reactor. In this work, a Lagrangian particle tracking tool recently developed in the
large eddy simulation (LES) framework of NGA is used to quantify the role of
cluster dynamics on biomass pyrolysis vapor catalytic upgrading in risers. This
numerical framework has been extensively validated for a range of
particle-laden flows, in particular, cluster fall velocities in risers of CFB
reactors have been shown to match experimental correlations (Fig.1). Two
configurations are investigated and compared: an
homogeneous system for which the catalyst-pyrolysis vapor contact time is statistically
uniform, and a pseudo-two-dimensional riser, such as shown in Fig.2, combining all
granular flow regimes of interest.

Figure 1:
Mean cluster fall velocity normalized by the minimum fluidization velocity as a
function of Archimedes number, a non-dimensional number that characterizes the
flow inertia due to density differences between the gas and solid phases. The solid line indicates a correlation developed from a range of
experimental studies by Noymer & Glicksman (2000).

Figure 2:
Pseudo two-dimensional simulation of a riser showing gas volume fraction (left)
and gas velocity magnitude (right). Particles are injected at the bottom where
the gas inlet is located.

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