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Multidimensional computations were carried out to simulate the in-cylinder fuel/air mixing process of a direct-injection spark-ignition engine using a modified version of the KIVA-3 code. A hollow cone spray was modeled using a Lagrangian stochastic approach with an empirical initial atomization treatment which is based on experimental data. Improved Spalding-type evaporation and drag models were used to calculate drop vaporization and drop dynamic drag. Spray/wall impingement hydrodynamics was accounted for by using a phenomenological model. Intake flows were computed using a simple approach in which a prescribed velocity profile is specified at the two intake valve openings. This allowed three intake flow patterns, namely, swirl, tumble and non-tumble, to be considered. It was shown that fuel vaporization was completed at the end of compression stroke with early injection timing under the chosen engine operating conditions.

Multidimensional modeling is used to study air-fuel mixing in a direct-injection spark-ignition engine. Emphasis is placed on the effects of the start of fuel injection on gas/spray interactions, wall wetting, fuel vaporization rate and air-fuel ratio distributions in this paper. It was found that the in-cylinder gas/spray interactions vary with fuel injection timing which directly impacts spray characteristics such as tip penetration and spray/wall impingement and air-fuel mixing. It was also found that, compared with a non-spray case, the mixture temperature at the end of the compression stroke decreases substantially in spray cases due to in-cylinder fuel vaporization. The computed trapped-mass and total heat-gain from the cylinder walls during the induction and compression processes were also shown to be increased in spray cases.

Gas-phase in-cylinder mixing was examined by two different methods. The first method for observing mixing involved planar Mie scattering measurements of the instantaneous number density of silicon oil droplets which were introduced to the in-cylinder flow. The local value of the number density was assumed to be representative of the local gas concentration. Because the objective was to observe the rate in which gas concentration gradients change, to provide gradients in number density, droplets were admitted into the engine through only one of the two intake ports. Air only flowed through the other port. Three different techniques were used in analyzing the droplet images to determine the spatially dependent particle number density. Direct counting, a filtering technique, and autocorrelation were used and compared. Further, numerical experiments were performed with the autocorrelation method to check its effectiveness for determination of particle number density.