In previous work, several significant improvements in the measurement of distillation curves for complex fluids were introduced. The modifications to the classical measurement provide for (1) temperature and volume measurements of low uncertainty, (2) temperature control based upon fluid behavior, and, most important, (3) a composition-explicit data channel in addition to the usual temperature-volume relationship. This latter modification is achieved with a new sampling approach that allows precise qualitative as well as quantitative analyses of each fraction, on the fly. Moreover, as part of the improved approach, the distillation temperature is measured in two locations. The temperature is measured in the usual location, at the bottom of the takeoff in the distillation head, but it is also measured directly in the fluid. The measurement in the fluid is a valid equilibrium thermodynamic state point that can be theoretically explained and modeled. The usual temperature measurement location (in the head) provides a temperature that is not a thermodynamic state point for a variety of reasons but which is comparable to historical measurements made for many decades. We also use a modification of the Sidney Young equation (to correct the temperatures to standard atmospheric pressure) in which explicit account is taken of the average length of the carbon chains of the fluid. In this paper, we have applied the advanced approach to samples of 91 AI gasoline and to mixtures of this gasoline with methanol (10 and 15%, vol/vol) as examples of oxygenates. On the individual fractions, we have done chemical analysis by gas chromatography (using flame ionization detection and mass spectrometry). For the methanol blends, the approach allows characterization of the azeotropic inflections in terms of fraction composition and energy content.

In this study, a novel approach was developed to formulate surrogate fuels having characteristics that are representative of diesel fuels produced from real-world refinery streams. Because diesel fuels typically consist of hundreds of compounds, it is difficult to conclusively determine the effects of fuel composition on combustion properties. Surrogate fuels, being simpler representations of these practical fuels, are of interest because they can provide a better understanding of fundamental fuel-composition and property effects on combustion and emissions-formation processes in internal-combustion engines. In addition, the application of surrogate fuels in numerical simulations with accurate vaporization, mixing, and combustion models could revolutionize future engine designs by enabling computational optimization for evolving real fuels. Dependable computational design would not only improve engine function, it would do so at significant cost savings relative to current optimization strategies that rely on physical testing of hardware prototypes. The approach in this study utilized the stateof-the-art techniques of 13 C and 1 H nuclear magnetic resonance spectroscopy and the advanced distillation curve to characterize fuel composition and volatility, respectively. The ignition quality was quantified by the derived cetane number. Two wellcharacterized, ultra-low-sulfur #2 diesel reference fuels produced from refinery streams were used as target fuels: a 2007 emissions certification fuel and a Coordinating Research Council (CRC) Fuels for Advanced Combustion Engines (FACE) diesel fuel. A surrogate was created for each target fuel by blending eight pure compounds. The known carbon bond types within the pure compounds, as well as models for the ignition qualities and volatilities of their mixtures, were used in a multiproperty regression algorithm to determine optimal surrogate formulations. The predicted and measured surrogate-fuel properties were quantitatively compared to the measured target-fuel properties, and good agreement was found.

The distillation (or boiling) curve of a complex fluid is a critically important indicator of the bulk behavior or response of the fluid. For this reason, the distillation curve, usually presented graphically as the boiling temperature against the volume fraction distilled, is often cited as a primary design and testing criterion for liquid fuels, lubricants, and other important industrial fluids. While the distillation curve gives a direct measure of fluid volatility fraction by fraction, the information the curve contains can be taken much further; there are numerous engineering and application-specific parameters that can be correlated to the distillation curve. When applied to liquid motor fuels, for example, one can estimate engine starting ability, drivability, fuel system icing and vapor lock, the fuel injector schedule, and fuel autoignition, etc. It can be used in environmental applications as a guide for blending virgin stock with reclaimed oil, guiding the formulation of product that will be suitable in various applications. Moreover, the distillation curve can be related to mutagenicity and the composition of the pollutant suite. It is therefore desirable to enhance or extend the usual approach to distillation curve measurement to allow optimal information content. In this paper, we present several modifications to the measurement of distillation curves that provide (1) temperature and volume measurement(s) of low uncertainty and, most important, (2) a composition-explicit data channel in addition to the usual temperature-volume relationship. This latter modification is achieved with a new sampling approach that allows precise qualitative as well as quantitative analyses of each fraction, on the fly. The analysis is done by gas chromatography coupled with specific or universal detectors. This second modification is the most significant change, since it is composition that is the most important underlying parameter that governs curve shape.

In a previous paper, a number of improvements in the method and apparatus used for the measurement of distillation curves for complex hydrocarbon fluid mixtures were presented. These improvements included the addition of a composition-explicit channel of data, improved temperature control and measurement, and improved and less uncertain volume measurement. In this paper, we demonstrate the improved approach with application to two complex hydrocarbon fluids, rocket propellant 1 (RP-1) and a synthetic JP-8 that is designated as S-8. RP-1 is a long-established hydrocarbon fuel that continues to be widely used since it was first developed in the 1950s. Modern versions of this fluid are produced from a narrow-range kerosene fraction that is processed to reduce unsaturated compounds and also sulfur-containing hydrocarbons. S-8 is a synthetic substitute for fluids such as JP-8 and Jet-A. It is produced with the Fischer Tropsch process from natural gas. As these new and reformulated fluids gain increasing application, especially in aviation/aerospace application, it will be increasingly important to have material characterization test procedures that are reproducible and that have a sound and fundamental basis. This will allow modeling of the properties and guide further refinement of the fluids.

We have recently introduced several important improvements in the measurement of distillation curves for complex fluids. The modifications to the classical measurement provide for (1) temperature and volume measurements of low uncertainty, (2) temperature control based upon fluid behavior, and, most important, (3) a composition-explicit data channel in addition to the usual temperature-volume relationship. This latter modification is achieved with a new sampling approach that allows precise qualitative as well as quantitative analyses of each fraction, on the fly. We have applied the new method to the measurement of rocket propellant, gasoline, and jet fuels. In this paper, we present the application of the technique to representative batches of the important aviation fuel Jet-A. The motivation behind the work is to provide a property database for the planned expansion of the use of military aviation fuel JP-8, which is nearly identical to Jet-A. JP-8 also contains an icing inhibitor, corrosion/lubricity enhancer, and antistatic additive. This fluid (JP-8) is currently the primary gas turbine fuel used by the United States Air Force and also naval shore-based aircraft. There is now interest in the United States Department of Defense to use this fuel for all military applications, including ground-based forces. This would mean use of JP-8 in tanks, armored personnel carriers, and other vehicles. This interest has renewed interest in the chemical and physical properties of JP-8, to facilitate adaptation and design. Since one of the most important design parameters for a fuel is the distillation curve, it is critical that the new approach be applied to the base fluid representative for JP-8, namely, Jet-A.

The primary objectives of this work were to formulate, blend, and characterize a set of four ultralow-sulfur diesel surrogate fuels in quantities sufficient to enable their study in single-cylinder-engine and combustion-vessel experiments. The surrogate fuels feature increasing levels of compositional accuracy (i.e., increasing exactness in matching hydrocarbon structural characteristics) relative to the single target diesel fuel upon which the surrogate fuels are based. This approach was taken to assist in determining the minimum level of surrogate-fuel compositional accuracy that is required to adequately emulate the performance characteristics of the target fuel under different combustion modes. For each of the four surrogate fuels, an approximately 30 L batch was blended, and a number of the physical and chemical properties were measured. This work documents the surrogate-fuel creation process and the results of the property measurements.

Fluid volatility is an important property of liquid fuels that previously has not been adequately addressed in the development of surrogate models for the thermophysical properties of these fluids. Especially important and timely is the development of surrogates for aviation fuels. In the present context, models refer to mathematical descriptions such as equations of state that provide a predictive capability. In this work, we demonstrate how the incorporation of volatility data, in the form of a distillation curve, leads to the development of improved surrogate models for aviation fuels. As an example, we present a seven-component surrogate mixture model for the thermophysical properties of a natural gas derived, synthetic aviation fuel known as S-8. We then compare the properties of the surrogate model with experimental density, sound speed, viscosity, thermal conductivity, and distillation curve data for the real fuel.

In previous work, several significant improvements in the measurement of distillation curves for complex fluids were introduced. The modifications to the classical measurement provide for (1) temperature and volume measurements of low uncertainty, (2) temperature control based upon fluid behavior with a model predictive temperature controller, and, most important, (3) a composition-explicit data channel in addition to the temperature-volume relationship that usually comprises the measurement. This latter modification was achieved with a new sampling approach that allows precise qualitative as well as quantitative analyses of each fraction, during the measurement of the distillation curve. In this paper, we utilize the composition-explicit information to characterize distillate cuts in terms of available energy content. This is critical information in the study of real fuels. The measure we use for the fluid energy content is the composite enthalpy of combustion for each component selected for identification in each distillate fraction. As a test system, we present the distillation cuts of two prepared mixtures of n-decane + n-tetradecane. Then, as a further illustration of the approach, we present an analysis of distillate fractions of a 91 antiknock index (AI) gasoline and a 91 AI gasoline with 15% methanol (vol/vol) added.