Investigating biomass composition and size effects on fast pyrolysis using global sensitivity analysis and CFD simulations

Liqiang Lu, Xi Gao, Aytekin Gel, Gavin M. Wiggins, Meagan Crowley, Brennan Pecha, Mehrdad Shahnam, William A. Rogers, James Parks, Peter N. Ciesielski

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

It is notoriously difficult to build an accurate universal model for biomass pyrolysis due to its sensitivity to a wide number of critical material attributes such as chemical species and physical sizes. In this work, a biomass pyrolysis kinetics with 32 heterogeneous reactions and 59 species was implemented in an open-source multiphase computational fluid dynamics (CFD) software MFiX and validated against two different experimental pyrolysis data sets that provided detailed data describing chemical component yields. The reaction scheme was then used to build a surrogate model and assess the sensitivity of pyrolysis yields to feedstock compositions. The sensitivity analysis determined that the yield of bio-char showed a strong positive sensitivity to the carbon-rich lignin and tannin pseudo-species in the reaction scheme while the bio-oil and bio-gas were correlated to oxygen-rich lignin pseudo-species. The reaction scheme was then integrated into a coarse-grained discrete element model to simulate fast pyrolysis in a bubbling fluidized bed over a range of feedstock particle sizes. The reactor simulations showed further sensitivity to particle size and hydrodynamics. Notably, particles under 0.5 mm have small heat transfer limitations but left the reactor before completely converting and thus reduced the bio-oil yield. Results from this study can be used to guide future development of highly accurate models for fast pyrolysis reactors with a variety of feedstock properties and operating conditions.

Original languageEnglish
Article number127789
JournalChemical Engineering Journal
Volume421
DOIs
StatePublished - Oct 1 2021

Funding

This research was conducted as part of the Feedstock-Conversion Interface Consortium (FCIC) funded by the U.S. Department of Energy ( DOE ) Bioenergy Technologies Office (BETO). This work was also supported by the U.S. Department of Energy , Office of Energy Efficiency and Renewable Energy, Bioenergy Technology Office under Contract No. DE-AC36-08GO28308 with the Alliance for Sustainable Energy, LLC. The authors would like to thank Dr. Debiagi from CRECK Modeling Group, The Polytechnic University of Milan, Italy for helpful discussions on the pyrolysis kinetics. This research was conducted as part of the Feedstock-Conversion Interface Consortium (FCIC) funded by the U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO). This work was also supported by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technology Office under Contract No. DE-AC36-08GO28308 with the Alliance for Sustainable Energy, LLC. The authors would like to thank Dr. Debiagi from CRECK Modeling Group, The Polytechnic University of Milan, Italy for helpful discussions on the pyrolysis kinetics. This work was funded by the Department of Energy, National Energy Technology Laboratory, an agency of the United States Government, through a support contract with Leidos Research Support Team (LRST). Neither the United States Government nor any agency thereof, nor any of their employees, nor LRST, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This work was funded by the Department of Energy, National Energy Technology Laboratory, an agency of the United States Government, through a support contract with Leidos Research Support Team (LRST). Neither the United States Government nor any agency thereof, nor any of their employees, nor LRST, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.

FundersFunder number
CRECK
Feedstock-Conversion Interface Consortium
LRST
Office of Energy Efficiency and Renewable Energy, Bioenergy Technology OfficeDE-AC36-08GO28308
Polytechnic University of Milan
U.S. Government
U.S. Department of Energy
Bioenergy Technologies Office
National Energy Technology Laboratory

    Keywords

    • Biomass
    • Fluidized bed
    • Kinetics
    • Pyrolysis
    • Sensitivity study
    • Surrogate model

    Fingerprint

    Dive into the research topics of 'Investigating biomass composition and size effects on fast pyrolysis using global sensitivity analysis and CFD simulations'. Together they form a unique fingerprint.

    Cite this