Sooting tendencies of diesel fuel component mixtures follow a linear mixing rule



With the growing importance of climate change, soot emissions from engines have been receiving increasing attention since black carbon is the second largest source of global warming. A sooting tendency can be used to quantify the extent of soot formation in a combustion device for a given fuel molecule, and therefore to quantify the soot reduction benefits of alternative fuels. However real fuels are complex mixtures of multiple components. In this work, we have used experimental methods to investigate how the sooting tendency of a blended fuel mixture is related to the sooting tendencies of the individual components. A test matrix was formulated that includes sixteen mixtures of six components that are representative of the main categories of hydrocarbons in diesel (eicosane (ECO) for alkanes, isocetane (ICE) for isoalkanes, butylcyclohexane (BCH) for cycloalkanes, 1-methylnaphthalene (1MN) for aromatics, tetralin for naphthoaromatics, and methyl-decanoate (MDC) for oxygenates). Most of the mixtures contain three to five components. The sooting tendency of each mixture was characterized by yield sooting index (YSI), which is based on the soot yield when a methane/air nonpremixed flame is doped with 1000 ppm of the test fuel. The YSIs were measured experimentally. The results show that the blending behavior is linear, i.e., the YSI of the mixtures is the mole-fraction-weighted average of the component YSIs. Experimental results have shown that the sooting tendency of a fuel mixture can be accurately estimated as the linear combination of the individual components. In addition, mass density of the mixtures is also measured, and a linear blending rule is applied to test whether mixing rules exist for mass density of diesel mixtures in this study. Results also have shown that the mixing rule tested in this study is valid and mass density of a mixture can be accurately estimated from the linear combination of the individual components.


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Supplementary material

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Supplemental Information Text
Experimental details, validation tests, tables of analyzed data
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Training set for YSI predictions
Database of measured sooting tendencies that were used for training the group contribution model