Partial Least-Squares Predictions of Nonpetroleum-Derived Fuel Content and Resultant Properties When Blended with Petroleum-Derived Fuels

Abstract

The U.S. Naval Research Laboratory has been engaged in a research program to develop sensor-based technologies to perform rapid automated fuel-quality surveillance. This approach is based on the development of quantitative models from the partial least-squares (PLS) regression of near-infrared (NIR) spectroscopic measurements of a representative calibration set of petroleum-derived fuels. As fuels from nonpetroleum sources become available it will be necessary to extend these chemometric models to accommodate Fischer-Tropsch (FT) synthetic fuels and biofuels. This extension is complicated by the fact that these new fuels will be initially introduced as blending components with petroleum-derived fuels. Chemometric modeling methodologies have been developed to identify and estimate the content of FT and biofuel present; then this information is used to estimate the bulk properties of the blends. With this approach, biodiesel content can be predicted, with respect to absolute error, to within 1.7% of its true value 95% of the time with a lower limit of detection of 1.5% using a single PLS model. The diesel fuel PLS property prediction models are applicable to diesel fuels blended with biodiesel fuel once that particular biodiesel fuel is incorporated in said models. The FT content in blends with petroleum fuels can be predicted, with respect to absolute error, to within 6.9% of its true value 95% of the time with a lower limit of detection of 15% using a series of paired PLS models for identification and quantification. In the presence of FT fuel, the PLS property models can be used after applying a correction factor that is derived from the identity and concentration of the FT fuel present.

Expanded Framework for the Prediction of Alternative Fuel Content and Alternative Fuel Blend Performance Properties Using Near-Infrared Spectroscopic Data

“…Thus, the hypothesis to be tested is that all predictions of alternative fuel content can be produced using jet-specific and diesel-specific PLS models calibrated to the percent content of any given alternative fuel type, including the predominant isoparaffinic fuels. These PLS models are used to evaluate fuel types in a specific order, much as was the case in the original work 9 , and if a model or model pair detects the presence of an alternative fuel in a sample, then this sample is not subjected to subsequent alternative fuel prediction models, as these subsequent models are, for the sake of accuracy, not constructed to take previously evaluated alternative fuel types fully into account.…”

“…In the original, FT-based work 9 , these coarse and fine model types were referred to as "identification" and "quantification" models, respectively. As implied by this former naming convention, the fine model's prediction results are used for all final quantitative predictions.…”

Novel Data Abstraction Strategy Utilizing Gas Chromatography–Mass Spectrometry Data for Fuel Property Modeling

“…This instrument was primarily trained on petrochemical fuels, but its capabilities were extended to accommodate a fuel population of Fischer−Tropsch (FT) synthetic fuels, fuels derived from biomass, and blends of these two fuel types with petrochemical fuels. 3 In addition, a discriminant model was incorporated into the NFPM to identify ultralow sulfur diesel (ULSD) fuels. 4 Despite what has previously been achieved with respect to fuel property predictions and generalized fuel quality and fitness monitoring, emerging fuels derived from biomass and other alternative sources present a significant challenge to predicting fuel properties from NIR spectra.…”

The Determination of a Diesel Solidifying Point by Near Infrared Spectroscopy

“…Different materials in the near infrared region is different in the absorption spectra. Each component has its own specific absorption characteristics, which is the foundation of NIR quantitative analysis (Cramer et al, 2009;Wu et al, 2009). Diesel oil is an important kind of engine fuel.…”