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A comprehensive biodiesel combustion model is presented for use in multi-dimensional engine simulations. The model incorporates realistic physical properties in a vaporization model developed for multi-component fuel sprays and applies an improved mechanism for biodiesel combustion chemistry. Previously, a detailed mechanism for methyl decanoate and methyl-9-decenoate was reduced from 3299 species to 85 species to represent the components of biodiesel fuel. In this work, a second reduction was performed to further reduce the mechanism to 69 species. Steady and unsteady spray simulations confirmed that the model adequately reproduced liquid penetration observed in biodiesel spray experiments. Additionally, the new model was able to capture expected fuel composition effects with low-volatility components and fuel blend sprays penetrating further.

A computational study was performed to evaluate the effects of bowl geometry, fuel spray targeting and swirl ratio under highly diluted, low-temperature combustion conditions in a heavy-duty diesel engine. This study is used to examine aspects of low-temperature combustion that are affected by mixing processes and offers insight into the effect these processes have on emissions formation and oxidation. The foundation for this exploratory study stems from a large data set which was generated using a genetic algorithm optimization methodology. The main results suggest that an optimal combination of spray targeting, swirl ratio and bowl geometry exist to simultaneously minimize emissions formation and improve soot and CO oxidation rates. Spray targeting was found to have a significant impact on the emissions and fuel consumption performance, and was furthermore found to be the most influential design parameter explored in this study.

The objective of this investigation is to optimize a light-duty diesel engine in order to minimize soot, NOx, carbon monoxide (CO), unburned hydrocarbon (UHC) emissions and peak pressure rise rate (PPRR) while improving fuel economy in a low oxygen environment. Variables considered are the injection timings, fractional amount of fuel per injection, half included spray angle, swirl, and stepped-bowl piston geometry. The KIVA-CHEMKIN code, a multi-dimensional computational fluid dynamics (CFD) program with detailed chemistry is used and is coupled to a multi-objective genetic algorithm (MOGA) along with an automated grid generator. The stepped-piston bowl allows more options for spray targeting and improved charge preparation. Results show that optimal combinations of the above variables exist to simultaneously reduce emissions and fuel consumption. Details of the spray targeting were found to have a major impact on the combustion process.

The objective of this investigation is to optimize light-duty diesel engine operating parameters using Adaptive Injection Strategies (AIS) for optimal fuel preparation. A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN code, is employed and a Multi-Objective Genetic Algorithm (MOGA) is used to study a Two-Stage Combustion (TSC) concept. The combustion process is considered at a light load operating condition (nominal IMEP of 5.5 bar and high speed (2000 rev/min)), and two combustion modes are combined in this concept. The first stage is ideally Homogeneous Charge Compression Ignition (HCCI) combustion and the second stage is diffusion combustion under high temperature and low oxygen concentration conditions. Available experimental data on a 1.9L single-cylinder research engine is used for model validation.

Homogeneous low temperature combustion is believed to be a promising approach to resolve the conflict of goals between high efficiency and low exhaust emissions. Disadvantageously for this kind of combustion, the whole process depends on chemical kinetics and thus is hard to control. Reactivity controlled combustion can help to overcome this difficulty. In the so-called RCCI (reactivity controlled compression ignition) combustion concept a small amount of pilot diesel that is injected directly into the combustion chamber ignites a highly diluted gasoline-air mixture. As the gasoline does not ignite without the diesel, the pilot injection timing and the ratio between diesel and gasoline can be used to control the combustion process. A phenomenological multi-zone model to predict RCCI combustion has been developed and validated against experimental and 3D-CFD data. The model captures the main physics governing ignition and combustion.

Simultaneous measurements of the radial and the tangential components of velocity are obtained in a high-speed, direct-injection diesel engine typical of automotive applications. Results are presented for engine operation with fuel injection, but without combustion, for three different swirl ratios and four injection pressures. With the mean and fluctuating velocities, the r-θ plane shear stress and the mean flow gradients are obtained. Longitudinal and transverse length scales are also estimated via Taylor's hypothesis. The flow is shown to be sufficiently homogeneous and stationary to obtain meaningful length scale estimates. Concurrently, the flow and injection processes are simulated with KIVA-3V employing a RNG k-ε turbulence model. The measured turbulent kinetic energy k, r-θ plane mean strain rates ( 〈Srθ〉, 〈Srr〉, and 〈Sθθ〉 ), deviatoric turbulent stresses , and the r-θ plane turbulence production terms are compared directly to the simulated results.

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.

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.

Two-dimensional computations of premixed-charge engine combustion were made using the KIVA-II code. The purpose of the study was to assess the influence of heat transfer and turbulence model boundary conditions on engine combustion predictions. Combustion was modeled using a laminar- and turbulent-characteristic-time model. Flow through the piston-cylinder-ring crevice was accounted for using a phenomenological crevice-flow model. The predictions were compared to existing cylinder pressure and wall heat transfer experimental data under motoring and fired conditions, at two engine speeds. Two different wall heat transfer model formulations were considered. The first is the standard wall function method. The second is based on solutions to the one-dimensional unsteady energy equation, formulated such that the standard wall function method is recovered in the quasi-steady limit. Turbulence was modeled using the standard k-ε turbulence model equations.

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.

Fuel spray atomization and breakup processes within a direct-injection spark-ignition (DISI) engine and outside the engine were modeled using a modified KIVA-3V code with improved spray models. The structures of the predicted sprays were qualitatively compared with planar images. The considered sprays were created by a prototype pressure-swirl injector and the planar images were obtained by laser sheet imaging in an optical DISI engine. In the out-of-engine case, the spray was injected into atmospheric air, and was modeled in a two dimensional bomb. In the engine case, the injection started from 270° ATDC, and full 3-D computations in the same engine were performed. In both cases, two liquid injection pressure conditions were applied, that is, 3.40 MPa and 6.12 MPa. The model gives good prediction of the tip penetration, and external spray shape, but the internal structure prediction has relatively lower accuracy, especially near the spray axis.

Multidimensional computations were made of spark-ignited premixed-charge combustion in a pancake-combustion-chamber engine with a centrally located spark plug and in two pent-roof-chamber engines, one with a central spark plug and the other with dual lateral spark plugs. A global combustion submodel was used that accounts for laminar kinetics and turbulent mixing effects. The predictions were compared with available measurements in the pancake-chamber engine over a range of loads, speeds, and equivalence ratios. In all cases the computed and measured cylinder pressures agreed well in trends and magnitudes (within 8%) for the entire duration of combustion. Fair agreements were also obtained between predicted and measured values of wall heat flux and emission index of nitric oxide. In the pent-roof-chamber engines the predicted maximum cylinder pressures also agreed well with measurements (within 12%) in cases with MBT (Minimum spark advance for Best Torque) or advanced spark timing.

Many studies have demonstrated ability of low temperature combustion to yield low NOx and soot while maintaining diesel-like thermal efficiencies. Methods of achieving low temperature combustion are numerous and range from using high cetane number fuels, like diesel, with large amounts of exhaust gas recirculation, to completely premixing a high octane number fuel, like gasoline, and approaching an HCCI-like condition. Both of the aforementioned techniques have relatively short combustion duration that results in very a rapid rate of heat release, and hence very rapid rates of pressure rise. This has been one of the major challenges for premixed, low temperature combustion at mid and high load. Reactivity Controlled Compression Ignition (RCCI) has been introduced recently, which is a dual fuel partially premixed combustion concept.

The potential of low temperature combustion to yield low NOx and soot while maintaining diesel-like thermal efficiencies has been demonstrated through countless studies. Methods of achieving low temperature combustion are just as numerous and they range from using high cetane number fuels, like diesel, with large amounts of exhaust gas recirculation, to completely premixing a high octane number fuel, like gasoline, and approaching an HCCI-like condition. The potential of operating a heavy-duty compression ignition engine fueled with conventional gasoline in a partially premixed combustion mode to have high thermal efficiency and low emissions has been demonstrated in this study. The objective of this work was to optimize the engine using computational tools. The KIVA3V-CHEMKIN code, a multi-dimensional engine CFD model was coupled to a Nondominated Sorting Genetic Algorithm (NSGA II), which is a multi-objective genetic algorithm.

A new ignition and combustion model has been developed and tested for use in premixed spark-ignition engines. The ignition model is referred to as the Discrete Particle Ignition Kernel (DPIK) model, and it uses Lagrangian markers to track the flame-front growth. The model includes the effects of electrode heat transfer on the early flame kernel growth process, and it is used in conjunction with a characteristic-time-scale combustion model once the ignition kernel has grown to a size where the effects of turbulence on the flame must be considered. A new term which accounts for the effect of air-fuel ratio, was added to the combustion model for modeling combustion in very lean and very rich mixtures. The flame kernel size predicted by the DPIK model was compared with measurements of Maly and Vogel. Furthermore, predictions of the electrode heat transfer were compared with data of Kravchik and Heywood. In both comparisons the model predictions were in good agreement with the experiments.

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.

An engine emissions and performance study was conducted in conjunction with a series of experiments using a constant volume cold spray chamber. The purpose of the study was to explore the effects of number of holes and hole size on the emissions and performance of a direct injection heavy duty diesel engine. The spray experiments provide insight into the spray parameters and their role in the engine's combustion processes. The fuel system used for both the engine and spray chamber experiments was an electronically controlled, common rail injector. The injector nozzle hole size and number combinations used in the experiments included 225X8 (225 gm diameter holes with 8 holes in the nozzle), 260X6, 260X8, and 30OX6. The engine tests were conducted on an instrumented single cylinder version of the Caterpillar 3400 series heavy duty diesel engine. Data were taken with the engine running at 1600 RPM, 75% load.

Stoichiometric combustion could enable a three-way catalyst to be used for treating NOx emissions of diesel engines, which is one of the most difficult species for diesel engines to meet future emission regulations. Previous study by Lee et al. [1] showed that diesel engines can operate with stoichiometric combustion successfully with only a minor impact on fuel consumption. Low NOx emission levels were another advantage of stoichiometric operation according to that study. In this study, the characteristics of stoichiometric diesel combustion were evaluated experimentally to improve fuel economy as well as exhaust emissions The effects of fuel injection pressure, boost pressure, swirl, intake air temperature, combustion regime (injection timing), and engine load (fuel mass injected) were assessed under stoichiometric conditions.

A study was performed to correlate the Sauter Mean Diameter (SMD), NOx and particulate emissions of a direct injection diesel engine with various injection pressures and different nozzle geometry. The spray experiments and engine emission tests were conducted in parallel using the same fuel injection system and same operating conditions. With high speed photography and digital image analysis, a light extinction technique was used to obtain the spray characteristics which included spray tip penetration length, spray angle, and overall average SMD for the entire spray. The NOx and particulate emissions were acquired by running the tests on a fully instrumented Caterpillar 3406 heavy duty engine. Experimental results showed that for higher injection pressures, a smaller SMD was observed, i.e. a finer spray was obtained. For this case, a higher NOx and lower particulate resulted.

Multidimensional modeling is used to study air-fuel mixing in a direct-injection spark-ignition engine. Emphasis is placed on the effects of the start of fuel injection on gas/spray interactions, wall wetting, fuel vaporization rate and air-fuel ratio distributions in this paper. It was found that the in-cylinder gas/spray interactions vary with fuel injection timing which directly impacts spray characteristics such as tip penetration and spray/wall impingement and air-fuel mixing. It was also found that, compared with a non-spray case, the mixture temperature at the end of the compression stroke decreases substantially in spray cases due to in-cylinder fuel vaporization. The computed trapped-mass and total heat-gain from the cylinder walls during the induction and compression processes were also shown to be increased in spray cases.