Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale
Abstract
Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveraging the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (≥ 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Then, using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against themore »
- Authors:
-
- Yale Univ., New Haven, CT (United States)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Publication Date:
- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States); Yale Univ., New Haven, CT (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V); National Science Foundation (NSF)
- OSTI Identifier:
- 1416906
- Alternate Identifier(s):
- OSTI ID: 1415227; OSTI ID: 1548871
- Report Number(s):
- NREL/JA-2700-70702
Journal ID: ISSN 0010-2180
- Grant/Contract Number:
- AC36-08GO28308; EE0007983; CBET 1604983
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- Combustion and Flame
- Additional Journal Information:
- Journal Volume: 190; Journal Issue: C; Journal ID: ISSN 0010-2180
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 09 BIOMASS FUELS; soot; biofuels; color ratio pyrometry; group contribution method; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 54 ENVIRONMENTAL SCIENCES; 33 ADVANCED PROPULSION SYSTEMS
Citation Formats
Das, Dhrubajyoti D., John, Peter C., McEnally, Charles S., Kim, Seonah, and Pfefferle, Lisa D. Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale. United States: N. p., 2017.
Web. doi:10.1016/j.combustflame.2017.12.005.
Das, Dhrubajyoti D., John, Peter C., McEnally, Charles S., Kim, Seonah, & Pfefferle, Lisa D. Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale. United States. https://doi.org/10.1016/j.combustflame.2017.12.005
Das, Dhrubajyoti D., John, Peter C., McEnally, Charles S., Kim, Seonah, and Pfefferle, Lisa D. 2017.
"Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale". United States. https://doi.org/10.1016/j.combustflame.2017.12.005. https://www.osti.gov/servlets/purl/1416906.
@article{osti_1416906,
title = {Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale},
author = {Das, Dhrubajyoti D. and John, Peter C. and McEnally, Charles S. and Kim, Seonah and Pfefferle, Lisa D.},
abstractNote = {Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveraging the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (≥ 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Then, using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against the unified database. The model’s predictive accuracy (as demonstrated by leave-one-out cross-validation) is comparable to a previously developed, more detailed predictive model. The fitted model provides insight into the effects of chemical structure on soot formation, and cases where its predictions fail reveal the presence of more complicated kinetic sooting mechanisms. Our work will therefore enable the rational design of low-sooting fuel blends from a wide range of feedstocks and chemical functionalities.},
doi = {10.1016/j.combustflame.2017.12.005},
url = {https://www.osti.gov/biblio/1416906},
journal = {Combustion and Flame},
issn = {0010-2180},
number = C,
volume = 190,
place = {United States},
year = {Wed Dec 06 00:00:00 EST 2017},
month = {Wed Dec 06 00:00:00 EST 2017}
}
Web of Science
Figures / Tables:
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