Abstract
Quantitative composition-property relationship of aviation hydrocarbon fuel consisting of hundreds of various hydrocarbons is one of the most important and challenging concerns for the rapid prediction of various specifications or other properties, and screening the suitable hydrocarbon fractions or classes for the specific application proposed. In this work, the detailed chemical compositions of seventeen kerosene-based hydrocarbon fuels were analyzed using the comprehensive two-dimensional gas chromatography coupled with quadruple mass spectrometry and flame ion detector (GC×GC–MS/FID), and hydrocarbons are classified by hydrocarbon classes (such as normal-paraffins, isoparaffins, cycloparaffins and substituted cycloparaffins) and carbon numbers (C7-C19) forming a series of composition matrices of their mass percentages. For each element of the matrix, a series of lumped compounds and the corresponding properties (density, freezing point, flash point and net heat of combustion) were defined according to the measured or theoretical properties of those similar hydrocarbons. The relationships between the detailed composition and the measured density, freezing point, flash point, and net heat of combustion of those kerosene-based hydrocarbon fuels were then established using the property matrices and several correlation algorithms. Compared with our previous work, it is found that the proposed quantitative composition-property relationship based on modified weighted average (MWA) method has achieved better performance in the predictions of density and the other specification properties with a higher determination coefficients and lower mean of absolute errors (MAE) of 0.82°C in prediction of freezing point, 0.0102MJ/kg in prediction of net heat of combustion and lower mean of absolute relative errors (MARE) of 0.2085% in prediction of density, 1.24% in prediction of flash point.
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