Published:Journal of Chromatographic Science,
ISSN 0021-9665Volume
39, Number 12, December 2001, pp. 501-507
Fuel Spill Identification Using Solid-Phase Extraction and Solid-Phase
Microextraction. I. Aviation Turbine Fuels
B.K. Lavine, D.M. Brzozowski,
J. Ritter, and A.J. Moores Department of Chemistry, Clarkson University, Potsdam, NY
13699-5810
H.T. Mayfield AL/EQ, 139 Barnes Drive, Suite 2, Tyndall AFB, FL 32403-5323
The water-soluble fraction of aviation jet fuels is examined
using solid-phase extraction and solid-phase microextraction. Gas chromatographic
profiles of solid-phase extracts and solid-phase microextracts of the water-soluble
fraction of kerosene- and nonkerosene-based jet fuels reveal that each jet fuel
possesses a unique profile. Pattern recognition analysis reveals fingerprint
patterns within the data characteristic of fuel type. By using a novel genetic
algorithm (GA) that emulates human pattern recognition through machine learning,
it is possible to identify features characteristic of the chromatographic profile
of each fuel class. The pattern recognition GA identifies a set of features
that optimize the separation of the fuel classes in a plot of the two largest
principal components of the data. Because principal components maximize variance,
the bulk of the information encoded by the selected features is primarily about
the differences between the fuel classes.
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