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In the present paper optimization tools are used to recommend low-emission engine combustion chamber designs, spray targeting and swirl ratio levels for a heavy-duty diesel engine operated at high-load. The study identifies aspects of the combustion and pollution formation that are affected by mixing processes, and offers guidance for better matching of the piston geometry with the spray plume geometry for enhanced mixing. By coupling a GA (genetic algorithm) with the KIVA-CFD code, and also by utilizing an automated grid generation technique, multi-objective optimizations with goals of low emissions and fuel economy were achieved. Three different multi-objective genetic algorithms including a Micro-Genetic Algorithm (μGA), a Nondominated Sorting Genetic Algorithm II (NSGA II) and an Adaptive Range Multi-Objective Genetic Algorithm (ARMOGA) were compared for conducting the optimization under the same conditions.

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.

Engine experiments have shown that with high-pressure multiple injections (two or more injection pulses per power cycle), the soot-NOx trade-off curves of a diesel engine can be shifted closer to the origin than those with the conventional single-pulse injections, reducing both soot and NOx emissions significantly. In order to understand the mechanism of emissions reduction, multidimensional computations were carried out for a heavy-duty diesel engine with multiple injections. Different injection schemes were considered, and the predicted cylinder pressure, heat release rate and soot and NOx emissions were compared with measured data. Excellent agreements between predictions and measurements were achieved after improvements in the models were made. The improvements include using a RNG k-ε turbulence model, adopting a new wall heat transfer model and introducing the nozzle discharge coefficient to account for the contraction of fuel jet at the nozzle exit.