Modeling the Influence of Molecular Interactions on the Vaporization of Multi-component Fuel Sprays Univ. of Wisconsin-Madison

Format:

Conference/Event

Author/Creator:

Jiao, Jiao, author.

Contributor:

Ra, Youngchul

Reitz, Rolf D.

Conference Name:

SAE 2011 World Congress & Exhibition (2011-04-12 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2011

Summary:

A vaporization model for realistic multi-component fuel sprays is described. The equilibrium at the interface between liquid droplets and the surrounding gas is obtained based on the UNIFAC method, which considers non-ideal molecular interactions that can greatly enhance or suppress the vaporization of the components in the system compared to predictions from ideal mixing using Raoult's Law, especially for polar fuels. The present results using the UNIFAC method are shown to be able to capture the azeotropic behaviors of polar molecule blends, such as mixtures of benzene and ethanol, benzene and iso-propanol, and ethanol and water [1]. Predicted distillation curves of mixtures of ethanol and multi-component gasoline surrogates are compared to those from experiments, and the model gives good improvements on predictions of the distillation curves for initial ethanol volume fractions ranging from 0% to 100%. The results show that the mixture tends to exhibit an azeotrope behavior which significantly influences the shape of the distillation curves, and expands the boiling point range due to the azeotrope behavior. Finally, the model is applied to spray cases in an engine with sweeps of injection timings and ambient pressures in order to investigate the conditions at which the consideration of UNIFAC exerts significant influence on the cylinder temperatures and the concentrations of the strong polar components of mixtures in the cylinder

Notes:

Vendor supplied data

Publisher Number:

2011-01-0387

Access Restriction:

Restricted for use by site license