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Title: Screening Fuels for Autoignition with Small-Volume Experiments and Gaussian Process Classification

Abstract

Partially reacting candidate fuels under highly dilute conditions across a range of temperatures provides a means to classify the candidates based on traditional ignition characteristics using much lower quantities (sub-mL) than the full octane tests. Using a classifier based on a Gaussian Process model, synthetic species profiles obtained by plug flow reactor simulations at seven temperatures are used to demonstrate that the configuration can be used to classify 95% of the samples correctly for autoignition sensitivity exceeding a threshold (S = 8) and 100%of the samples correctly for research octane number exceeding a threshold (RON = 90). Molecular beam mass spectrometry (MBMS) experimental data at four temperatures is then used as the model input in a real-world test. Despite the nontrivial relationship between the MBMS measurements and speciation as well as experimental noise it is still possible to classify 95% of the samples correctly for RON and 85% of the samples correctly for S in a 'leave-one-out' cross validation exercise. The test data set consists of 45 fuels and includes a variety of primary reference fuels, ethanol blends and other oxygenates.

Authors:
 [1];  [2]; ORCiD logo [2]; ORCiD logo [3];  [4]; ORCiD logo [4]
  1. Department of Mathematics, The University of Arizona, Tucson, Arizona 85721, United States
  2. Transportation and Hydrogen Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
  3. Bioenergy Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
  4. High Performance Algorithms and Complex Fluids Group, Computational Science Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1476247
Report Number(s):
NREL/JA-2C00-71286
Journal ID: ISSN 0887-0624
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article
Journal Name:
Energy and Fuels
Additional Journal Information:
Journal Volume: 32; Journal Issue: 9; Journal ID: ISSN 0887-0624
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; Gaussian distribution; mass spectrometry; molecular beams; statistical tests

Citation Formats

Lunderman, Spencer, Fioroni, Gina M., McCormick, Robert L., Nimlos, Mark R., Rahimi, Mohammad J., and Grout, Ray W. Screening Fuels for Autoignition with Small-Volume Experiments and Gaussian Process Classification. United States: N. p., 2018. Web. doi:10.1021/acs.energyfuels.8b02112.
Lunderman, Spencer, Fioroni, Gina M., McCormick, Robert L., Nimlos, Mark R., Rahimi, Mohammad J., & Grout, Ray W. Screening Fuels for Autoignition with Small-Volume Experiments and Gaussian Process Classification. United States. doi:10.1021/acs.energyfuels.8b02112.
Lunderman, Spencer, Fioroni, Gina M., McCormick, Robert L., Nimlos, Mark R., Rahimi, Mohammad J., and Grout, Ray W. Tue . "Screening Fuels for Autoignition with Small-Volume Experiments and Gaussian Process Classification". United States. doi:10.1021/acs.energyfuels.8b02112.
@article{osti_1476247,
title = {Screening Fuels for Autoignition with Small-Volume Experiments and Gaussian Process Classification},
author = {Lunderman, Spencer and Fioroni, Gina M. and McCormick, Robert L. and Nimlos, Mark R. and Rahimi, Mohammad J. and Grout, Ray W.},
abstractNote = {Partially reacting candidate fuels under highly dilute conditions across a range of temperatures provides a means to classify the candidates based on traditional ignition characteristics using much lower quantities (sub-mL) than the full octane tests. Using a classifier based on a Gaussian Process model, synthetic species profiles obtained by plug flow reactor simulations at seven temperatures are used to demonstrate that the configuration can be used to classify 95% of the samples correctly for autoignition sensitivity exceeding a threshold (S = 8) and 100%of the samples correctly for research octane number exceeding a threshold (RON = 90). Molecular beam mass spectrometry (MBMS) experimental data at four temperatures is then used as the model input in a real-world test. Despite the nontrivial relationship between the MBMS measurements and speciation as well as experimental noise it is still possible to classify 95% of the samples correctly for RON and 85% of the samples correctly for S in a 'leave-one-out' cross validation exercise. The test data set consists of 45 fuels and includes a variety of primary reference fuels, ethanol blends and other oxygenates.},
doi = {10.1021/acs.energyfuels.8b02112},
journal = {Energy and Fuels},
issn = {0887-0624},
number = 9,
volume = 32,
place = {United States},
year = {2018},
month = {8}
}