Abstract

A handheld near-infrared (NIR) analyzer was used to build partial least squares (PLS) models relating jet fuel properties to the spectral data (880–1570 nm). The properties included: API gravity, % aromatics, cetane index, density, 10%/50%/90% recovered distillation temperatures, freezing point, flashpoint, hydrogen content, and % saturates. The models were validated using leave-one-out validation of the training sets and by predicting an independent test set of fuels. The repeatability of the developed NIR methods was determined by performing replicate measurements on a single master analyzer. The reproducibility of the NIR methods was determined by performing measurements on multiple samples using five different analyzers. The results indicate that the NIR methods are useful for rapid monitoring of jet fuel quality at commercial airports during transport, storage, and distribution.

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