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Diesel fuels are complex mixtures of thousands of hydrocarbons. Since modeling their combustion characteristics with the inclusion of all hydrocarbon species is not feasible, a hybrid surrogate model approach is used in the present work to represent the physical and chemical properties of three different diesel fuels by using up to 13 and 4 separate hydrocarbon species, respectively. The surrogates are arrived at by matching their distillation profiles and important properties with the real fuel, while the chemistry surrogates are arrived at by using a Group Chemistry Representation (GCR) method wherein the hydrocarbon species in the physical property surrogates are grouped based on their chemical classes, and the chemistry of each class is represented by using up to two hydrocarbon species.

The effect of piston ring pack crevice flow and lubricant oil vaporization on heavy-duty diesel engine deposits is investigated numerically using a multidimensional CFD code, KIVA3V, coupled with Chemkin II, and computational grids that resolve part of the crevice region appropriately. Improvements have been made to the code to be able to deal with the complex geometry of the ring pack, and sub-models for the crevice flow dynamics, lubricating oil vaporization and combustion, soot formation and deposition were also added to the code. Eight parametric cases were simulated under reacting conditions using detailed chemical kinetics to determine the effects of variations of lube-oil film thickness, distribution of the oil film thickness, number of injection pulses, and the main injection timing on engine soot deposition. The results show that crevice-borne hydrocarbon species play an important role in deposit formation on crevice surfaces.

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.

A correction for the turbulence dissipation, based on non-equilibrium turbulence considerations from rapid distortion theory, has been derived and implemented in combination with the RNG k - ε model in a KIVA-based code. This model correction has been tested and compared with the standard RNG k - ε model for the compression and the combustion phase of two heavy duty DI diesel engines. The turbulence behavior in the compression phase shows clear improvements over the standard RNG k - ε model computations. In particular, the macro length scale is consistent with the corresponding time scale and with the turbulent kinetic energy over the entire compression phase. The combustion computations have been performed with the characteristic time combustion model. With this dissipation correction no additional adjustments of the turbulent characteristic time model constant were necessary in order to match experimental cylinder pressures and heat release rates of the two engines.

The low temperature combustion concept is very attractive for reducing NOx and soot emissions in diesel engines. However, it has potential limitations due to higher combustion noise, CO and HC emissions. A multiple injection strategy is an effective way to reduce unburned emissions and noise in LTC. In this paper, the effect of multiple injection strategies was investigated to reduce combustion noise and unburned emissions in LTC conditions. A hybrid surrogate fuel model was developed and validated, and was used to improve LTC predictions. Triple injection strategies were considered to find the role of each pulse and then optimized. The split ratio of the 1st and 2nd pulses fuel was found to determine the ignition delay. Increasing mass of the 1st pulse reduced unburned emissions and an increase of the 3rd pulse fuel amount reduced noise. It is concluded that the pulse distribution can be used as a control factor for emissions and noise.