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Title: Reduced Chemistry for Butanol Isomers at Engine-Relevant Conditions

Abstract

Butanol has received significant research attention as a second-generation biofuel in the past few years. In the present study, skeletal mechanisms for four butanol isomers were generated from two widely accepted, well-validated detailed chemical kinetic models for the butanol isomers. The detailed models were reduced using a two-stage approach consisting of the directed relation graph with error propagation and sensitivity analysis. During the reduction process, issues were encountered with pressure-dependent reactions formulated using the logarithmic pressure interpolation approach; these issues are discussed and recommendations are made to avoid ambiguity in its future implementation in mechanism development. The performance of the skeletal mechanisms generated here was compared with that of detailed mechanisms in simulations of autoignition delay times, laminar flame speeds, and perfectly stirred reactor temperature response curves and extinction residence times, over a wide range of pressures, temperatures, and equivalence ratios. Good agreement was observed between the detailed and skeletal mechanisms, demonstrating the adequacy of the resulting reduced chemistry for all the butanol isomers in predicting global combustion phenomena. In addition, the skeletal mechanisms closely predicted the time-histories of fuel mass fractions in homogeneous compression-ignition engine simulations. The performance of each butanol isomer was additionally compared with that of amore » gasoline surrogate with an antiknock index of 87 in a homogeneous compression-ignition engine simulation. The gasoline surrogate was consumed faster than any of the butanol isomers, with tert-butanol exhibiting the slowest fuel consumption rate. As a result, while n-butanol and isobutanol displayed the most similar consumption profiles relative to the gasoline surrogate, the two literature chemical kinetic models predicted different orderings.« less

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [4]
  1. Beihang Univ., Beijing (China)
  2. Oregon State Univ., Corvallis, OR (United States)
  3. Univ. of Connecticut, Storrs, CT (United States); Innovative Scientific Solutions Inc., Dayton, OH (United States)
  4. Univ. of Connecticut, Storrs, CT (United States)
Publication Date:
Research Org.:
Energy Frontier Research Centers (EFRC) (United States). Combustion Energy Frontier Research Center (CEFRC)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1397186
Grant/Contract Number:  
SC0001198
Resource Type:
Accepted Manuscript
Journal Name:
Energy and Fuels
Additional Journal Information:
Journal Volume: 31; Journal Issue: 1; Related Information: CEFRC partners with Princeton University (lead); Argonne National Laboratory; University of Connecticut; Cornell University; Massachusetts Institute of Technology; University of Minnesota; Sandia National Laboratories; University of Southern California; Stanford University; University of Wisconsin, Madison; Journal ID: ISSN 0887-0624
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS

Citation Formats

Hui, Xin, Niemeyer, Kyle E., Brady, Kyle B., and Sung, Chih -Jen. Reduced Chemistry for Butanol Isomers at Engine-Relevant Conditions. United States: N. p., 2016. Web. doi:10.1021/acs.energyfuels.6b01857.
Hui, Xin, Niemeyer, Kyle E., Brady, Kyle B., & Sung, Chih -Jen. Reduced Chemistry for Butanol Isomers at Engine-Relevant Conditions. United States. https://doi.org/10.1021/acs.energyfuels.6b01857
Hui, Xin, Niemeyer, Kyle E., Brady, Kyle B., and Sung, Chih -Jen. Mon . "Reduced Chemistry for Butanol Isomers at Engine-Relevant Conditions". United States. https://doi.org/10.1021/acs.energyfuels.6b01857. https://www.osti.gov/servlets/purl/1397186.
@article{osti_1397186,
title = {Reduced Chemistry for Butanol Isomers at Engine-Relevant Conditions},
author = {Hui, Xin and Niemeyer, Kyle E. and Brady, Kyle B. and Sung, Chih -Jen},
abstractNote = {Butanol has received significant research attention as a second-generation biofuel in the past few years. In the present study, skeletal mechanisms for four butanol isomers were generated from two widely accepted, well-validated detailed chemical kinetic models for the butanol isomers. The detailed models were reduced using a two-stage approach consisting of the directed relation graph with error propagation and sensitivity analysis. During the reduction process, issues were encountered with pressure-dependent reactions formulated using the logarithmic pressure interpolation approach; these issues are discussed and recommendations are made to avoid ambiguity in its future implementation in mechanism development. The performance of the skeletal mechanisms generated here was compared with that of detailed mechanisms in simulations of autoignition delay times, laminar flame speeds, and perfectly stirred reactor temperature response curves and extinction residence times, over a wide range of pressures, temperatures, and equivalence ratios. Good agreement was observed between the detailed and skeletal mechanisms, demonstrating the adequacy of the resulting reduced chemistry for all the butanol isomers in predicting global combustion phenomena. In addition, the skeletal mechanisms closely predicted the time-histories of fuel mass fractions in homogeneous compression-ignition engine simulations. The performance of each butanol isomer was additionally compared with that of a gasoline surrogate with an antiknock index of 87 in a homogeneous compression-ignition engine simulation. The gasoline surrogate was consumed faster than any of the butanol isomers, with tert-butanol exhibiting the slowest fuel consumption rate. As a result, while n-butanol and isobutanol displayed the most similar consumption profiles relative to the gasoline surrogate, the two literature chemical kinetic models predicted different orderings.},
doi = {10.1021/acs.energyfuels.6b01857},
journal = {Energy and Fuels},
number = 1,
volume = 31,
place = {United States},
year = {Mon Dec 12 00:00:00 EST 2016},
month = {Mon Dec 12 00:00:00 EST 2016}
}

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