TY - GEN
T1 - Simulation-based engineering of biomass fast pyrolysis reactors
AU - Gao, X.
AU - Lu, L.
AU - Parks, J.
AU - Shahnam, M.
AU - Syamlal, M.
N1 - Publisher Copyright:
© 2020 American Institute of Chemical Engineers. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Stuart Daw initiated the Computational Pyrolysis Consortium (CPC) over seven years ago (1) to help address thechallenges posed by fast pyrolysis of biomass feedstocks and the catalytic upgrading of the bio-oil product. The multi-national laboratory consortium, with support from EERE’s Biomass Energy Technologies office, combinedexperimental and computational techniques to improve the fast pyrolysis process, improve bio-oil properties andcomponent utilization, and develop tools and understanding of the scale-up and integration of component reactorssupporting commercialization of catalytic fast pyrolysis systems. Since its inception, the CPC has broadened itsmembership and scope to address a range of biomass energy challenges as represented by its new name:Consortium for Computational Physics and Chemistry (CCPC) (2). At the invitation of Dr. Daw, NETL joined the CCPCin 2017 to assist in the application of multiphase computational fluid dynamics (CFD) tools to study pyrolysis andcatalytic upgrading reactors. In this work, in collaboration with the CCPC, NETL uses its MFiX Suite of multiphase flowCFD tools to study two experimental pyrolysis systems being operated at DOE’s National Renewable EnergyLaboratory. One reactor, a laboratory-scale bubbling fluid bed of biomass and sand, provides a platform to studyfundamental pyrolysis over a range of biomass feedstocks and operating conditions. The second reactor is anentrained flow device for supplying pyrolysis gases for catalytic processing at the near-pilot scale. Particle drag modelsapplicable to biomass, sand, and char were developed to accurately model solids hydrodynamics. A detailed pyrolysischemistry mechanism (3) has been incorporated in the simulations to predict a broad range of product species thatcomprise the bio-oil, bio-gas, and bio-char products. Simulation results and comparison to experimental data arepresented. Excellent agreement for both reactor systems was obtained. These tools are now being used to supportdevelopment of pyrolysis reactor systems at larger scales using a broad range of forest product feedstocks.
AB - Stuart Daw initiated the Computational Pyrolysis Consortium (CPC) over seven years ago (1) to help address thechallenges posed by fast pyrolysis of biomass feedstocks and the catalytic upgrading of the bio-oil product. The multi-national laboratory consortium, with support from EERE’s Biomass Energy Technologies office, combinedexperimental and computational techniques to improve the fast pyrolysis process, improve bio-oil properties andcomponent utilization, and develop tools and understanding of the scale-up and integration of component reactorssupporting commercialization of catalytic fast pyrolysis systems. Since its inception, the CPC has broadened itsmembership and scope to address a range of biomass energy challenges as represented by its new name:Consortium for Computational Physics and Chemistry (CCPC) (2). At the invitation of Dr. Daw, NETL joined the CCPCin 2017 to assist in the application of multiphase computational fluid dynamics (CFD) tools to study pyrolysis andcatalytic upgrading reactors. In this work, in collaboration with the CCPC, NETL uses its MFiX Suite of multiphase flowCFD tools to study two experimental pyrolysis systems being operated at DOE’s National Renewable EnergyLaboratory. One reactor, a laboratory-scale bubbling fluid bed of biomass and sand, provides a platform to studyfundamental pyrolysis over a range of biomass feedstocks and operating conditions. The second reactor is anentrained flow device for supplying pyrolysis gases for catalytic processing at the near-pilot scale. Particle drag modelsapplicable to biomass, sand, and char were developed to accurately model solids hydrodynamics. A detailed pyrolysischemistry mechanism (3) has been incorporated in the simulations to predict a broad range of product species thatcomprise the bio-oil, bio-gas, and bio-char products. Simulation results and comparison to experimental data arepresented. Excellent agreement for both reactor systems was obtained. These tools are now being used to supportdevelopment of pyrolysis reactor systems at larger scales using a broad range of forest product feedstocks.
UR - http://www.scopus.com/inward/record.url?scp=85106168853&partnerID=8YFLogxK
M3 - 会议稿件
AN - SCOPUS:85106168853
T3 - AIChE Annual Meeting, Conference Proceedings
BT - 2020 Virtual AIChE Annual Meeting
PB - American Institute of Chemical Engineers
T2 - 2020 AIChE Annual Meeting
Y2 - 16 November 2020 through 20 November 2020
ER -
