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With recent increases in global fuel prices there has become a growing interest in expanding the use of diesel engines in the transportation industry. However, new engine development is costly and time intensive, requiring many hours of expensive engine tests. The ability to accurately predict an engine's performance based on existing models would reduce the expense involved in creating a new engine of different size. In the present study experimental results from two single-cylinder direct injection diesel engines were used to examine previously developed engine scaling models. The first scaling model was based on an equal spray penetration correlation. The second model considered both equal spray penetration and flame lift-off length. The engines used were a heavy-duty Caterpillar engine with a 2.44L displacement and a light-duty GM engine with a 0.48L displacement.

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.

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 nonintrusive diagnostic technique has been developed by which dynamic axial piston-position and tilt-angle measurements have been made in a single-cylinder research engine. A laser beam, introduced into the combustion chamber through an optical port in the cylinder head, was reflected by a polished surface on the piston crown. Motion of the reflected beam, carrying with it information on piston position and piston tilt, was monitored by a set of receiving optics. Piston motion was studied as a function of both engine speed and cylinder pressure (i.e., piston loading.) Measured axial piston-position was found to deviate from the theoretical position calculated from the measured crank-shaft position owing to the effects of tilt and piston loading. Furthermore, evidence of piston veer (tilt of the piston in a plane parallel to the axis of the wrist pin) was observed, which had an effect on the accuracy of the axial piston-position measurement.

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.

A single cylinder CFR research engine has been run in HCCI combustion mode at the rich and the lean limits of the homogeneous charge operating range. To achieve a variation of the degree of charge stratification, two GDI injectors were installed: one was used for generating a homogeneous mixture in the intake system, and the other was mounted directly into the side of the combustion chamber. At the lean limit of the operating range, stratification showed a tremendous improvement in IMEP and emissions. At the rich limit, however, the stratification was limited by the high-pressure rise rate and high CO and NOx emissions. In this experiment the location of the DI injector was in such a position that the operating range that could be investigated was limited due to liquid fuel impingement onto the piston and liner.

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.

A dual fuel engine simulation model was formulated and the combustion process of a diesel/natural gas dual fuel engine was studied using an updated KIVA-3V Computational Fluid Dynamic (CFD) code. The dual fuel engine ignition and combustion process is complicated since it includes diesel injection, atomization and ignition, superimposed with premixed natural gas combustion. However, understanding of the combustion process is critical for engine performance optimization. Starting from a previously validated Characteristic-Timescale diesel combustion model, a natural gas combustion model was implemented and added to simulate the ignition and combustion process in a dual fuel bus engine. Available engine test data were used for validation of both the diesel-only and the premixed spark-ignition operation regimes. A new formulation of the Characteristic-Timescale combustion model was then introduced to allow smooth transition between the combustion regimes.

The present study uses a numerical model to investigate the effects of flow turbulence on premixed iso-octane HCCI engine combustion. Different levels of in-cylinder turbulence are generated by using different piston geometries, namely a disc-shape versus a square-shape bowl. The numerical model is based on the KIVA code which is modified to use CHEMKIN as the chemistry solver. A detailed reaction mechanism is used to simulate the fuel chemistry. It is found that turbulence has significant effects on HCCI combustion. In the current engine setup, the main effect of turbulence is to affect the wall heat transfer, and hence to change the mixture temperature which, in turn, influences the ignition timing and combustion duration. The model also predicts that the combustion duration in the square bowl case is longer than that in the disc piston case which agrees with the measurements.

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.

Numerical simulations are performed to investigate the fuel/air mixing preparation in a gasoline direct injection (GDI) engine. A two-valve OHV engine with wedge combustion chamber is investigated since automobiles equipped with this type of engine are readily available in the U.S. market. Modifying and retrofitting these engines for GDI operation could become a viable scenario for some engine manufactures. A pressure-swirl injector and wide spacing injection layout are adapted to enhance mixture preparation. The primary interest is on preparing the mixture with adequate equivalence ratio at the spark plug under a wide range of engine operating conditions. Two different engine operating conditions are investigated with respect to engine speed and load. A modified version of the KIVA-3V multi-dimensional CFD code is used. The modified code includes the Linearized Instability Sheet Atomization (LISA) model to simulate the development of the hollow cone spray.

A multi-objective genetic algorithm coupled with the KIVA3V release 2 code was used to optimize the piston bowl geometry, spray targeting, and swirl ratio levels of a high speed direct injected (HSDI) diesel engine for passenger cars. Three modes, which represent full-, mid-, and low-loads, were optimized separately. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. High throughput computing was conducted using the CONDOR software. An automated grid generator was used for efficient mesh generation with variable geometry parameters, including open and reentrant bowl designs. A series of new spray models featuring reduced mesh dependency were also integrated into the code. A characteristic-time combustion (CTC) model was used for the initial optimization for time savings. Model validation was performed by comparison with experiments for the baseline engine at full-, mid-, and low-load operating conditions.

A combustion chamber geometry design optimization study has been performed on a high-speed direct-injection (HSDI) automotive diesel engine at a part-load medium-speed operating condition using both modeling and experiments. A model-based optimization was performed using the KIVA-GA code. This work utilized a newly developed 6-parameter automated grid generation technique that allowed a vast number of piston geometries to be considered during the optimization. Other salient parameters were included that are known to have an interaction with the chamber geometry. They included the start of injection (SOI) timing, swirl ratio (SR), exhaust gas recirculation percentage (EGR), injection pressure, and the compression ratio (CR). The measure of design fitness used included NOx, soot, unburned hydrocarbon (HC), and CO emissions, as well as the fuel consumption. Subsequently, an experimental parametric study was performed using the piston geometry found by the numerical optimization.

Schlieren visualization was performed to investigate hydrogen injection into a quiescent chamber. The injection pressures investigated were 52 and 104 bar, and the chamber density ranged from 1.15 to 12.8 kg/m3, giving rise to underexpanded jets for all conditions. The expansion waves outside the nozzle were clearly visible with hydrogen, and the effect was confirmed with studies of nitrogen injected into a nitrogen environment. The distance between the expansion wave fronts was found to scale directly with the ratio of the exit pressure to the chamber pressure. The jet tip penetration rate was measured and was found to increase with injection pressure, and decrease with chamber density as expected. A mass- and momentum-preserving scheme was developed to relate the underexpanded jet to a subsonic jet of larger diameter.