The correct representation of a fuel, in terms of its physical and chemical properties and its combustion kinetics poses, a challenge to modern engine development when state-of-the-art simulation technology is used. In this context, a promising approach is the use of surrogates that emulate the properties of real fuels, where the surrogates are made up of a significantly lower number of components than the original fuels. The goal of this paper is to present an algorithm that can be used to generate surrogates composed of real chemical components, as opposed to pseudo components.The algorithm was developed by simultaneously fitting the True Boiling Point (TBP) curve, the liquid density at 15 ℃ and the cetane number. To illustrate the algorithm, surrogates for four different fuels were generated: a commercially available European diesel and three research diesel proposed by the FACE (Fuels for Advanced Combustion Engines) CRC Research Group. Two of the resulting surrogates were produced on a lab-scale and subjected to laboratory examination. For validation, the experimental data for these two surrogates were compared to those for the target fuels and to data generated by thermodynamic models on the basis of the surrogates' compositions.Both the fitted properties and additional properties, which were not used for fitting, were compared with experimental properties such as the ASTM D86 boiling curve, content of aromatics, flash point, heating value, cloud point, viscosity, and tempera-

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Discrete modeling is a concept to establish thermodynamics on Shannon entropy expressed by variables that characterize discrete states of individual molecules in terms of their interacting neighbors in a mixture. To apply this method to condensed-phase lattice fluids, this paper further develops an approach proposed by Vinograd which features discrete Markov-chains for the sequential lattice construction and rigorous use of Shannon information as thermodynamic entropy, providing an in-depth discussion of the modeling concept evolved. The development comprises (1) improved accuracy compared to Monte Carlo data and (2) an extension from a two-dimensional to a three-dimensional simple lattice. The resulting model outperforms the quasichemical approximation proposed by Guggenheim, a frequently used reference model for the simple case of spherical molecules with uniform energetic surface properties. To illustrate its potential as a starting point for developing g E -models in chemical engineering applications, the proposed modeling methodology is extended, using the example of a simple approach for dicelike lattice molecules with multiple interaction sites on their surfaces, to address more realistic substances. A comparison with Monte Carlo simulations shows the model's capability to distinguish between isomeric configurations, which is a promising basis for future g E -model development in view of activity coefficients for liquid mixtures.

Thermodynamic modeling of extensive systems usually implicitly assumes the additivity of entropy. Furthermore, if this modeling is based on the concept of Shannon entropy, additivity of the latter function must also be guaranteed. In this case, the constituents of a thermodynamic system are treated as subsystems of a compound system, and the Shannon entropy of the compound system must be subjected to constrained maximization. The scope of this paper is to clarify prerequisites for applying the concept of Shannon entropy and the maximum entropy principle to thermodynamic modeling of extensive systems. This is accomplished by investigating how the constraints of the compound system have to depend on mean values of the subsystems in order to ensure additivity. Two examples illustrate the basic ideas behind this approach, comprising the ideal gas model and condensed phase lattice systems as limiting cases of fluid phases. The paper is the first step towards developing a new approach for modeling interacting systems using the concept of Shannon entropy.