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Technical Paper

Numerical Modeling of Fuel Sprays in DISI Engines Under Early-Injection Operating Conditions

2000-03-06
2000-01-0273
Numerical calculations of the fuel spray structure from a high-pressure swirl injector were used to enable the interpretation of experimental observations obtained in hot, hollow-cone fuel sprays issued into sub-atmospheric-pressure environments. The experiments show that the spray becomes narrower, more compact, but with a relatively long penetration depth. Model input parameters, including the droplet size distribution, early vapor production, and initial cone angle, were modified to determine which spray characteristics are important in recreating observed spray structures. A very small mean droplet diameter is needed to recreate the experimentally observed structure of the high-temperature, low-pressure sprays. Vapor addition to the emerging spray is then required to increase the axial penetration and provide the observed vapor core.
Technical Paper

Effect of Operating Conditions and Fuel Type on Crevice HC Emissions: Model Results and Comparison with Experiments

1999-10-25
1999-01-3578
A one-dimensional model for crevice HC post-flame oxidation is used to calculate and understand the effect of operating parameters and fuel type (propane and isooctane) on the extent of crevice hydrocarbon and the product distribution in the post flame environment. The calculations show that the main parameters controlling oxidation are: bulk burned gas temperatures, wall temperatures, turbulent diffusivity, and fuel oxidation rates. Calculated extents of oxidation agree well with experimental values, and the sensitivities to operating conditions (wall temperatures, equivalence ratio, fuel type) are reasonably well captured. Whereas the bulk gas temperatures largely determine the extent of oxidation, the hydrocarbon product distribution is not very much affected by the burned gas temperatures, but mostly by diffusion rates. Uncertainties in both turbulent diffusion rates as well as in mechanisms are an important factor limiting the predictive capabilities of the model.
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