A new strategy of characterizing hydrocarbon fuels using FTIR spectra and generalized linear model with grouped-Lasso regularization

In previous studies, we have shown that gas-phase mid-infrared spectra can be used to estimate the properties of hydrocarbon fuels. Specifically, the spectrum around 3.4 mu m and regularized linear models were utilized to estimate various physical and chemical properties of hydrocarbon fuels. In this study, we use a generalized linear model with grouped-Lasso regularization to characterize the average fuel structure in terms of the fractions of each functional group type and provide a new strategy to approach the property estimation problem. The robustness of this structure characterization method against low spectral resolution and high multiplicative noise in FTIR spectra are studied and presented. Two property estimation models, i.e. a linear and a nonlinear additive model, are presented as demonstrations of estimating properties from functional group numbers.

Automated summary

The study demonstrates the use of gas-phase mid-infrared spectra for estimating the properties of hydrocarbon fuels and proposes a new strategy for property estimation. It characterizes fuel structure using a generalized linear model with grouped-Lasso regularization and investigates the robustness of the method against low spectral resolution and high multiplicative noise. Two property estimation models, linear and nonlinear additive models, are presented to estimate properties based on functional group numbers.