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The effects of different Research Octane Number [RON] fuels on a multi-cylinder light-duty compression ignition [CI] engine were investigated at light load conditions. Experiments were conducted on a GM 1.9L 4-cylinder diesel engine at Argonne National Laboratory, using two different fuels, i.e., 75 RON and 93 RON. Emphasis was placed on 5 bar BMEP load, 2000 rev/min engine operation using two different RON fuels, and 2 bar BMEP load operating at 1500 rev/min using 75 RON gasoline fuel. The experiments reveal difficulty in controlling combustion at low load points using the higher RON fuel. In order to explain the experimental trends, simulations were carried out using the KIVA3V-Chemkin Computational Fluid Dynamics [CFD] Code. The numerical results were validated with the experimental results and provided insights about the engine combustion characteristics at different speeds and low load conditions using different fuels.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline (termed GDICI for Gasoline Direct-Injection Compression Ignition) in the low temperature combustion (LTC) regime is presented. As an aid to plan engine experiments at full load (16 bar IMEP, 2500 rev/min), exploration of operating conditions was first performed numerically employing a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion. Operation ranges of a light-duty diesel engine operating with GDICI combustion with constraints of combustion efficiency, noise level (pressure rise rate) and emissions were identified as functions of injection timings, exhaust gas recirculation rate and the fuel split ratio of double-pulse injections.

Several diffusion combustion scaling models were experimentally tested in two geometrically similar single-cylinder diesel engines with a bore diameter ratio of 1.7. Assuming that the engines have the same in-cylinder thermodynamic conditions and equivalence ratio, the combustion models primarily change the fuel injection pressure and engine speed in order to attain similar performance and emissions. The models tested include an extended scaling model, which scales diffusion flame lift-off length and jet spray penetration; a simple scaling model, which only scales spray penetration at equal mean piston speed; and a same speed scaling model, which holds crankshaft rotational velocity constant while also scaling spray penetration. Successfully scaling diffusion combustion proved difficult to accomplish because of apparent differences that remained in the fuel-air mixing and heat transfer processes.

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%.

RNG k-ε closure turbulence dissipation equations are evaluated employing the CFD code KIVA-3V Release 2. The numerical evaluations start by considering simple jet flows, including incompressible air jets and compressible helium jets. The results show that the RNG closure turbulence model predicts lower jet tip penetration than the "standard" k-ε model, as well as being lower than experimental data. The reason is found to be that the turbulence kinetic energy is dissipated too slowly in the downstream region near the jet nozzle exit. In this case, the over-predicted R term in RNG model becomes a sink of dissipation in the ε-equation. As a second step, the RNG turbulence closure dissipation models are further tested in complex engine flows to compare against the measured evolution of turbulence kinetic energy, and an estimate of its dissipation rate, during both the compression and expansion processes.