Sentence examples for surrogate formulation from inspiring English sources

The proposed surrogate formulation methodology is denoted as the Minimalist Functional Group MFGG) approach.

This simplifies the process of surrogate formulation, facilitates surrogate testing, and significantly reduces the size and time involved in developing chemical kinetic models by reducing the number of thermochemical and kinetic parameters requiring estimation.

The appropriateness of the surrogate formulation technique is demonstrated by the experimental measurement of various gas phase combustion kinetic phenomena of the proposed surrogate mixture and of the target Jet-A fuel:.

A strong correlation was observed between the YSI and the relative abundance of different types of carbon atoms (as quantified by 1H and 13C NMR spectroscopy) in these fuels and compounds, indicating that such NMR characterization can capture essential structure-specific sooting information of relevance to surrogate formulation.

The results demonstrate that the four CPTs currently used in aviation kerosene surrogate formulation - H/C molar ratio, derived cetane number (DCN), average molecular weight (MW), and threshold sooting index (TSI) - effectively constrain the chemical functional group distribution of the fuel, and, hence, the global combustion behaviors of pre-vaporized fuel/air mixtures.

In this work, we present a novel approach for surrogate fuel formulation by matching target fuel functional groups, while minimizing the number of surrogate species.

The extinction limits of diffusion flames have been measured experimentally and computed numerically for fuels of three different molecular structures pertinent to surrogate fuel formulation: n-alkanes, alkyl benzenes, and iso-octane.

A methodology for the formulation of surrogate fuels for the emulation of real fuel gas phase combustion kinetic phenomena pertinent to gas turbine combustion is described and tested.

This limited amount of information is generated using a medium level fidelity method, namely a panel method plus a boundary layer formulation, but the surrogate only uses the drag information and is independent of both the method used to generate this information and the specific problem that is considered for illustration.

It is important that information about the sooting tendency of the target fuel be incorporated in the formulation of these surrogates.

An MILP formulation is developed including surrogate models based on the detailed NLP steady state models.