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Hydraulically intensified medium pressure common rail (MPCR) electronic fuel injection systems are an attractive concept for heavy-duty diesel engine applications. They offer excellent packaging flexibility and thorough engine management system integration. Two different concepts were evaluated in this study. They are different in how the pressure generation and injection events are related. One used a direct principle, where the high-pressure generation and injection events occur simultaneously producing a near square injection rate profile. Another concept was based on an indirect principle, where potential energy (pressure) is first stored inside a hydraulic accumulator, and then released during injection, as a subsequent event. A falling rate shape is typically produced in this case. A unit pump, where the hydraulic intensifier is separated from the injector by a high-pressure line, and a unit injector design are considered for both concepts.

A multi-objective genetic algorithm methodology was applied to a heavy-duty diesel engine at three different operating conditions of interest. Separate optimizations were performed over various fuel injection nozzle parameters, piston bowl geometries and swirl ratios (SR). Different beginning of injection (BOI) timings were considered in all optimizations. The objective of the optimizations was to find the best possible fuel economy, NOx, and soot emissions tradeoffs. The input parameter ranges were determined using design of experiment methodology. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. For the optimization of piston bowl geometry, an automated grid generator was used for efficient mesh generation with variable geometry parameters. The KIVA3V release 2 code with improved ERC sub-models was used. The characteristic time combustion (CTC) model was employed to improve computational efficiency.

The combustion and emissions of a diesel/natural gas dual-fuel engine are studied. Available engine experimental data demonstrates that the dual-fuel configuration provides a potential alternative to diesel engine operation for reducing emissions. The experiments are compared to multi-dimensional model results. The computer code used is based on the KIVA-3V code and consists of updated sub-models to simulate more accurately the fuel spray atomization, auto-ignition, combustion and emissions processes. The model results show that dual-fuel engine combustion and emissions are well predicted by the present multi-dimensional model. Significant reduction in NOx emissions is observed in both the experiments and simulations when natural gas is substituted for diesel fuel. The HC emissions are under predicted by numerical model as the natural gas substitution is increased.

The effect of injection rate shape on spray evolution and emission characteristics is investigated and a methodology for active control of fuel injection is proposed. Extensive validation of advanced vaporization and primary jet breakup models was performed with experimental data before studying the effects of systematic changes of injection rate shape. Excellent agreement with the experiments was obtained for liquid and vapor penetration lengths, over a broad range of gas densities and temperatures. Also the predicted flame lift-off lengths of reacting diesel fuel sprays were in good agreement with the experiments. After the validation of the models, well-defined rate shapes were used to study the effect of injection rate shape on liquid and vapor penetration, flame lift-off lengths and emission characteristics.

The recently developed KIVA-GA computer code was used in the current study to optimize the combustion chamber geometry of a heavy -duty diesel truck engine and a high-speed direct-injection (HSDI) small-bore diesel engine. KIVA-GA performs engine simulations within the framework of a genetic algorithm (GA) global optimization code. Design fitness was determined using a modified version of the KIVA-3V code, which calculates the spray, combustion, and emissions formation processes. The measure of design fitness includes NOx, unburned HC, and soot emissions, as well as fuel consumption. The simultaneous minimization of these factors was the ultimate goal. The KIVA-GA methodology was used to optimize the engine performance using nine input variables simultaneously. Three chamber geometry related variables were used along with six other variables, which were thought to have significant interaction with the chamber geometry.

A new primary breakup model was developed and applied to simulate the diesel fuel spray and atomization process. The continuous liquid fuel jet was simulated by a discrete Lagrangian particle method, and the primary breakup of the jet was calculated using a new 1-D Eulerian method that provides the jet breakup time and drop size distribution. A set of correlations of the breakup characteristics, including the breakup time and drop size, were developed for a range of operating conditions. The correlations were then used in the KIVA code to predict the jet primary breakup. For drop secondary breakups, the Kelvin-Helmholtz/Rayleigh-Taylor hybrid model was employed. The new primary breakup model was first validated by comparison to experimental breakup length and jet liquid tip penetration lengths. Predictions of the new breakup model were also compared with experimental data and predictions of the standard breakup model.

An optimization study combining multidimensional CFD modeling and a global, evolutionary search technique known as the Genetic Algorithm has been carried out. The subject of this study was a 2-stroke, spark-ignited, direct-injection, single-cylinder research engine (SCRE). The goal of the study was to optimize the part load operating parameters of the engine in order to achieve the lowest possible emissions, improved fuel economy, and reduced wall heat transfer. Parameters subject to permutation in this study were the start-of-injection (SOI) timing, injection duration, spark timing, fuel injection angle, dwell between injections, and the percentage of fuel mass in the first injection pulse. The study was comprised of three cases. All simulations were for a part load, intermediate-speed condition representing a transition operating regime between stratified charge and homogeneous charge operation.

A radiation model based on the Discrete Ordinates Method (DOM) was incorporated into the KIVA3v multidimensional code to study the effects of soot and radiation on diesel engine performance at high load. A thermophoretic soot deposition model was implemented to predict soot concentrations in the near-wall region, which was found to affect radiative heat flux levels. Realistic, non-uniform combustion chamber wall surface temperature distributions were predicted using a finite-element-based heat conduction model for the engine metal components that was coupled with KIVA3v in an iterative scheme. The more accurate combustion chamber wall temperatures enhanced the accuracy of both the radiation and soot deposition models as well as the convective heat transfer model. For a basline case, (1500 rev/min, 100% load) it was found that radiation can account for as much as 30% of the total wall heat loss and that soot deposition in each cycle is less than 3% of the total in-cylinder soot.

Fuel Injection System (FIS) research on injection pressure, timing control, and rate shaping, and studies on the modeling of injector nozzle flows and their effect on fuel spray characteristics are usually conducted separately. Only recently has the fuel injection and spraying process been studied as a complete system, i.e., including both the high-pressure fuel delivery and its effect on the nozzle flow characteristics, including nozzle cavitation. A methodology for coupling the fuel injection system and its effect on spray characteristics is presented here. The method is applied to an example case of a conventional pump-line-nozzle system. Mathematical models for characterizing the flows from the pump to the nozzle are formulated and solved using the Method of Characteristics and finite difference techniques. The nozzle internal flow is modeled using zero-dimensional flow models, in which the nozzle cavitation and its effect on the nozzle exit flow are accounted for.