Genetic algorithms applied to pattern recognition analysis of high-speed gas chromatograms of aviation turbine fuels using an integrated Jet-A/JP-8 database

High-speed gas chromatography was used to develop a potential method to typ e civilian and military jet fuels. A database of 212 gas chromatograms of n eat jet fuel samples representing common aviation turbine fuels found in th e United States (Jet-A, JP-5, JP-7, JP-8, and JPTS) was mined using a genet ic algorithm, which was necessary because of the similarities of the gas ch romatograms in the database. Principal-component models developed from gas chromatography peaks identified by the genetic algorithm were able to corre ctly classify the gas chromatograms of neat jet fuels, and these models wer e also able to successfully classify the gas chromatograms of jet fuels tha t had undergone weathering in a subsurface environment. The present study, which is a logical extension of an earlier effort was undertaken because of the change from JP-4 to JP-8 as the principal U.S. Air Force fuel. (C) 199 9 Academic Press.