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We present a model that predicts the research and motor octane numbers of a wide variety of gasoline process streams and their blends including oxygenates based on detailed composition. The octane number is correlated to a total of 57 hydrocarbon lumps measured by gas chromatography. The model is applicable to any gasoline fuel regardless of the refining process it originates from. It is based on the analysis of 1471 gasoline fuels from different naphtha process streams such as reformates, cat-naphthas, alkylates, isomerates, straight runs, and various hydroprocessed naphthas. Blends of these individual process streams are also considered in this work. The model predicts the octane number within a standard error of 1 number for both the research and motor octane numbers.

The method of structure-oriented lumping (SOL) for describing the compositions, chemical reactions, and properties of complex hydrocarbon mixtures has been extended to molecules found in vacuum residua. The SOL approach was initially developed for gas oil and lighter fractions (i.e., those boiling at <1100 °F), where molecular compositions can be organized in terms of homologous series of single-core molecules (e.g., benzene and alkylated benzenes). In this work, residua molecules are represented as multicore molecules comprising linked assemblies of singlecore species. The original SOL molecular description, using vectors of structural increments, is retained, along with the addition of information about the core linkages, and the extension meshes seamlessly with the conventional SOL notation. Using this formalism, properties of residua may be readily calculated and kinetic models of residua conversion processes developed.

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We have developed a simple composition-based model for predicting the cetane number of diesel fuels with general applicability to any diesel fuel regardless of the refining process it originates from. The cetane number is correlated to a total of 129 different hydrocarbon lumps determined by a combination of supercritical fluid chromatography, gas chromatography, and mass spectroscopic methods. A total of 203 diesel fuels are considered in this study derived from various diesel-range refinery process streams and their commercial blends. Across the multitude of such process streams and blends, the model predicts the cetane number with a standard error of 1.25 numbers, which is well within the experimental error of the measurement.