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This paper is a continuation of an earlier paper, which examined the steady-state internal heat transfer in the exhaust system of a diesel powered, light-duty vehicle. The present paper deals with the heat transfer of the exhaust system during two types of transient testing, as well as, the estimation of the exhaust systems external heat transfer. Transient heat transfer was evaluated using: a simple fuel-step transient under constant speed and the New European Driving Cycle (NEDC). The thermal response of the external walls varied considerably for the various components of the exhaust system. The largest percent difference between the measured temperatures and the corresponding quasi-steady estimates were about 10%, which is attributed to thermal storage. Allowing for thermal storage resulted in an excellent agreement between measurements and analysis.

Multi-dimensional computational efforts using comprehensive and skeletal kinetics have been made to investigate the cool flame region in HCCI combustion. The work was done in parallel to an experimental study that showed the impact of the negative temperature coefficient and the cool flame on the start of combustion using different fuels, which is now the focus of the simulation work. Experiments in a single cylinder CFR research engine with n-butane and a primary reference fuel with an octane number of 70 (PRF 70) were modeled. A comparison of the pressure and heat release traces of the experimental and computational results shows the difficulties in predicting the heat release in the cool flame region. The behavior of the driving radicals for two-stage ignition is studied and is compared to the behavior for a single-ignition from the literature. Model results show that PRF 70 exhibits more pronounced cool flame heat release than n-butane.

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.

A cylinder model was developed using artificial neural networks (ANN). The cylinder model utilized the trained ANN models to predict engine parameters including cylinder pressures, cylinder temperatures, cylinder wall heat transfer, NOx and soot emissions. The ANN models were trained to approximate CFD simulation results of an engine. The ANN cylinder model was then applied to predict engine performance and emissions over the standard heavy-duty FTP transient cycle. The engine responses varying over the engine speed and torque range were simulated in the course of the transient test cycle. It was demonstrated that the ANN cylinder model is capable of simulating the characteristics of the engine operating under transient conditions reasonably well.

The KIVA 3V code has been applied to predict combustion chamber heat flux in an air-cooled utility engine. The KIVA heat flux predictions were compared with experimentally measured data in the same engine over a wide range of operating conditions. The measured data were found to be approximately two times larger than the predicted results, which is attributed to the omission of chemical heat release in the near-wall region for the heat transfer model applied. Modifying the model with a simple scaling factor provided a good comparison with the measured data for the full range of engine load, heat flux sensor location, air-fuel ratio and spark timings tested. The detailed spatially resolved results of the KIVA predictions were then used to develop a simplified model of the combustion chamber temporally integrated heat flux using an artificial neural network (ANN).

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.

Experimental data is used in conjunction with multi-dimensional modeling in a modified version of the KIVA-3V code to characterize the emissions behavior of a high-speed, direct-injection diesel engine. Injection pressure and EGR are varied across a range of typical small-bore diesel operating conditions and the resulting soot-NOx tradeoff is analyzed. Good agreement is obtained between experimental and modeling trends; the HSDI engine shows increasing soot and decreasing NOx with higher EGR and lower injection pressure. The model also indicates that most of the NOx is formed in the region where the bulk of the initial heat release first takes place, both for zero and high EGR cases. The mechanism of NOx reduction with high EGR is shown to be primarily through a decrease in thermal NOx formation rate.

Detailed chemical kinetics was implemented in the KIVA-3V multidimensional CFD code to study the combustion process in Homogeneous Charge Compression Ignition (HCCI) engines. The CHEMKIN code was implemented such that the chemistry and flow solutions were coupled. Detailed reaction mechanisms were used to simulate the fuel chemistry of ignition and combustion. Effects of turbulent mixing on the reaction rates were also considered. The model was validated using the experimental data from two modified heavy-duty diesel engines, including a Volvo engine and a Caterpillar engine operated at the HCCI mode. The results show that good levels of agreement were obtained using the present KIVA/CHEMKIN model for a wide range of engine conditions, including various fuels, injection systems, engine speeds, and EGR levels. Ignition timings were predicted well without the need to adjust any kinetic constants.

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.

Many commercial fuels, including gasoline and diesel, are multicomponent hydrocarbons. During the fuel vaporization process, the volatile components evaporate first, which dominate the region near the nozzle exit. The lately evaporated vapor with high penetration has high molecular weight. Thus, ignition and combustion of multicomponent fuels are not only influenced by distribution of fuel vapor mass fraction, but also by distribution of the components. This paper presents a spark ignition and combustion model with consideration of such multicomponent effects for GDI engines. Ignition kernel growth due to flame front propagation is considered in the model to eliminate the sensitivity of the numerical mesh size on the results.

A single cylinder CFR research engine has been run in HCCI combustion mode for a range of temperatures and fuel compositions. The data indicate that the best HCCI operation, as measured by a combination of successful combustion with low ISFC, occurs at or near the rich limit of operation. Analysis of the pressure and heat release histories indicated the presence, or absence, and impact of the fuel's NTC ignition behavior on establishing successful HCCI operation. The auto-ignition trends observed were in complete agreement with previous results found in the literature. Furthermore, analysis of the importance of the fuel's octane sensitivity, through assessment of an octane index, successfully explained the changes in the fuels auto-ignition tendency with changes in engine operating conditions.

Artificial neural networks (ANN) have been recognized as universal approximators for nonlinear continuous functions and actively applied in engine research in recent years [1, 2, 3, 4, 5, 6, 7 and 8]. This paper describes the methodology and results of using the ANN to model a turbocharged DI diesel engine. The engine was simulated using the CFD code (KIVA-ERC) over a wide range of operating conditions, and numerical simulation results were used to train the ANN. An efficient data collection methodology using the Design of Experiments (DOE) techniques was developed to select the most characteristic engine operating conditions and hence the most informative data to train the ANN. This approach minimizes the time and cost of collecting training data from either computational or experimental resources. The trained ANN was then used to predict engine parameters such as cylinder pressure, cylinder temperature, NOx and soot emissions, and cylinder heat transfer.

A computational optimization study was performed for a direct-injection diesel engine using a recently developed 1-D-KIVA3v-GA (1-Dimensional-KIVA3v-Genetic Algorithm) computer code. The code performs a full engine cycle simulation within the framework of a genetic algorithm (GA) code. Design fitness is determined using a 1-D (one-dimensional) gas dynamics code for the simulation of the gas exchange process, coupled with the KIVA3v code for three-dimensional simulations of spray, combustion and emissions formation. The 1-D-KIVA3v-GA methodology was used to simultaneously investigate the effect of eight engine input parameters on emissions and performance for four cases, which include cases at 2500 RPM and 1000 RPM, with both simulated at high-load and low-load conditions.

An experimental and numerical characterization has been conducted for high-pressure hydraulically actuated fuel injection systems. One single and one double-guided multi-hole Valve-Covered-Orifice (VCO) type injector was used with a Common Rail (CR) injection system, and two mini-sac injectors for Hydraulic electronic Unit Injection system (HEUI) were used with different orifice diameters. The purpose of the study was to explore the effects of the injection system and the operating conditions on the engine emissions for a direct injection small bore diesel engine. The diesel spray was injected into a pressurized chamber with optical access at ambient temperature. The gas density inside the chamber was representative of the density in a High Speed Direct Injection (HSDI) diesel engine at the time of injection. The experimental spray parameters included: injection pressure, injection duration, nozzle type, and nozzle diameter.

An improved discrete particle ignition kernel (DPIK) model and the G-equation combustion model have been developed and implemented in KIVA-3V. In the ignition model, the spark ignition kernel growth is tracked by Lagrangian markers and the spark discharge energy and flow turbulence effects on the ignition kernel growth are considered. The predicted ignition kernel size was compared with the available measurements and good agreement was obtained. Once the ignition kernel grows to a size where the turbulent flame is fully developed, the level set method (G-equation) is used to track the mean turbulent flame propagation. It is shown that, by ignoring the detailed turbulent flame brush structure, fine numerical resolution is not needed, thus making the models suitable for use in multidimensional modeling of SI engine combustion.

This study considers combustion processes in a heavy-duty diesel engine at various low emissions operating conditions. The start-of-injection timings varied from -20 to 5 ATDC while the EGR levels varied from 6% to 44%. At certain conditions, HCCI-like combustion characteristics were observed under which low emissions could be achieved. The numerical model used is an improved version of KIVA-3V that can simulate spray breakup and mixture autoignition over a wide range of conditions. The ignition and combustion processes were simulated using both detailed and standard (simplified) chemistry models. Model results show that engine combustion and emissions can be predicted reasonably well under the current conditions. The trends of NOx and soot emissions with respect to the injection timings and EGR levels were well captured. However, it was found that the model over-predicted the NOx emissions in certain early injection cases.

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 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.

A level set G-equation model has been developed to model the combustion process in spark ignition engines. The spark ignition process was modeled using an improved version of the Discrete Particle Ignition Kernel (DPIK) model. The two models were implemented into the KIVA-3V code to simulate SI engine combustion under both premixed and direct injection conditions. In the ignition model, the ignition kernel growth is tracked by Lagrangian markers, and spark discharge energy and flow turbulence effects on the kernel growth are considered. Once the ignition kernel grows to a size where the turbulent flame is fully developed, the G-equation model is used to track the mean turbulent flame evolution. When combined with a characteristic time scale combustion model, the models were also used to simulate stratified combustion in DISI engines, where the triple flame structure must be considered.

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.