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The 3-Zones Extended Coherent Flame Model (ECFM3Z) and the Tabulated Kinetics for Ignition (TKI) auto-ignition model are widely used for RANS simulations of reactive flows in Diesel engines. ECFM3Z accounts for the turbulent mixing between one zone that contains compressed air and EGR and another zone that contains evaporated fuel. These zones mix to form a reactive zone where combustion occurs. In this mixing zone TKI is applied to predict the auto-ignition event, including the ignition delay time and the heat release rate. Because it is tabulated, TKI can model complex fuels over a wide range of engine thermodynamic conditions. However, the ECFM3Z/TKI combustion modeling approach requires an efficient predictive spray injection calculation. In a Diesel direct injection engine, the turbulent mixing and spray atomization are mainly driven by the liquid/gas coupling phenomenon that occurs at moving liquid/gas interfaces.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

Flow field asymmetry can lead to an asymmetric mixture preparation in Diesel engines. To understand the evolution of this asymmetry, it is necessary to characterize the in-cylinder flow over the full compression stroke. Moreover, since bowl-in-piston cylinder geometries can substantially impact the in-cylinder flow, characterization of these flows requires the use of geometrically correct pistons. In this work, the flow has been visualized via a transparent piston top with a realistic bowl geometry, which causes severe experimental difficulties due to the spatial and temporal variation of the optical distortion. An advanced optical distortion correction method is described to allow reliable particle image velocimetry (PIV) measurements through the full compression stroke. Based on the ensemble-averaged velocity results, flow asymmetry characterized by the swirl center offset and the associated tilting of the vortex axis is quantified.

CAE tools are increasingly important in the automotive design process. In part, CAE tools can be useful in reducing the number of physical prototypes required during a product development effort. CFD tools can assess and predict cylinder charge motion for proposed designs, thereby limiting the need for prototype work. Though detailed combustion simulation results could help guide product development, the time required for such simulations limits their usefulness in the context of a production program. However equally valuable information can be obtained from gas exchange analyses which require less computation time and are run only from Intake Valve opening (IVO) to spark timing. Chemical kinetics is not included in this type of analysis. Using this approach, large numbers of configurations can be evaluated in a short period of time. Every passing year automotive engineers are challenged to attain higher fuel economy targets.

The current trend of downsizing used in gasoline engines, while reducing fuel consumption and CO2 emissions, imposes severe thermal loads inside the combustion chamber. These critical thermodynamic conditions lead to the possible auto-ignition (AI) of fresh gases hot-spots around Top-Dead-Center (TDC). At this very moment where the surface to volume ratio is high, wall heat transfer influences the temperature field inside the combustion chamber. The use of a realistic wall temperature distribution becomes important in the case of a downsized engine where fresh gases hot spots found near high temperature walls can initiate auto-ignition. This paper presents a comprehensive numerical methodology for an accurately prediction of thermodynamic conditions inside the combustion chamber based on Conjugate Heat Transfer (CHT).

A, three-dimensional CFD code, based on the KIVA code, is used to explore alternatives to conventional DI diesel engine designs for reducing NOx and soot emissions without sacrificing engine performance. The effects of combustion chamber design and fuel spray orientation are investigated using a new proposed GAMMA engine concept, and two new multiple injector combustion system (MICS) designs which utilize multiple injectors to increase gas motion and enhance fuel/air mixing in the combustion chamber. From these computational studies, it is found that both soot and nitrous oxide emissions can be significantly reduced without the need for more conventional emission control strategies such as EGR or ultra high injection pressure. The results suggest that CFD models can be a useful tool not only for understanding combustion and emissions production, but also for investigating new design concepts.

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.

This paper implements a coupled approach to integrate the internal nozzle flow and the ensuing fuel spray using a Volume-of-Fluid (VOF) method in the CONVERGE CFD software. A VOF method was used to model the internal nozzle two-phase flow with a cavitation description closed by the homogeneous relaxation model of Bilicki and Kestin [1]. An Eulerian single velocity field approach by Vallet et al. [2] was implemented for near-nozzle spray modeling. This Eulerian approach considers the liquid and gas phases as a complex mixture with a highly variable density to describe near nozzle dense sprays. The mean density is obtained from the Favreaveraged liquid mass fraction. The liquid mass fraction is transported with a model for the turbulent liquid diffusion flux into the gas.

A set of reduced chemical mechanisms was developed for use in multi-dimensional engine simulations of premixed gasoline combustion. The detailed Primary Reference Fuel (PRF) mechanism (1034 species, 4236 reactions) from Lawrence Livermore National Laboratory (LLNL) was employed as the starting mechanism. The detailed mechanism, referred to here as LLNL-PRF, was reduced using a technique known as Parallel Direct Relation Graph with Error Propagation and Sensitivity Analysis. This technique allows for efficient mechanism reduction by parallelizing the ignition delay calculations used in the reduction process. The reduction was performed for a temperature range of 800 to 1500 K and equivalence ratios of 0.5 to 1.5. The pressure range of interest was 0.75 bar to 40 bar, as dictated by the wide range in spark timing cylinder pressures for the various cases. In order to keep the mechanisms relatively small, two reductions were performed.

Lagrangian particle tracking has proven very useful for IC engine spray simulations. However, traditional techniques have been very susceptible to grid dependency. As a consequence, predicted engine performance can depend on the computational mesh. The two main causes of this problem are the collision algorithm and the inter-phase coupling. Using the No Time Counter droplet collision algorithm with an embedded collision mesh practically eliminates grid dependency as a consequence of the collision algorithm. The remaining grid dependency is due to numerical error of the gas phase near the injector and problems with coupling the gas phase and liquid phase. Calculations were made using a novel interpolation scheme that takes advantage of the polar symmetry in the spray. The scheme transforms the velocities into their polar components before doing interpolation. The results show a dramatic decrease in grid dependency.

An ultrahigh injection pressure, common rail fuel injection system was designed, fabricated, and evaluated. The result was a system suitable for high-power density diesel engine applications. The main advantages of the concept are a very short injection duration capability, high injection pressure independent of engine speed, a simplified electronic control valve, and good packaging flexibility. Two prototype injectors were developed. Tests were performed on an injector flow bench and in a single cylinder research engine. The first prototype delivered 320 mm3 within 2.5 milliseconds with a 2600 bar peak injection pressure. A conventional minisac nozzle was used. The second prototype employed a specially designed pintle nozzle producing a near-zero cone angle liquid jet impinging on a 9-mm cylindrical target centered on the piston bowl crown (OSKA-S system). The second prototype had the capability to deliver 316mm3 in 0.97ms.

Using gasoline and diesel simultaneously in a dual-fuel combustion system has shown effective benefits in terms of both brake thermal efficiency and exhaust emissions. In this study, the dual-fuel approach is applied to a light-duty spark ignition (SI) gasoline direct injection (GDI) engine. Three combustion modes are proposed based on the engine load, diesel micro-pilot (DMP) combustion at high load, SI combustion at low load, and diesel assisted spark-ignition (DASI) combustion in the transition zone. Major focus is put on the DMP mode, where the diesel fuel acts as an enhancer for ignition and combustion of the mixture of gasoline, air, and recirculated exhaust gas. Computational fluid dynamics (CFD) is used to simulate the dual-fuel combustion with the final goal of supporting the comprehensive optimization of the main engine parameters.

The present study extends the recently developed KIVA-GA computer code to incorporate a generalized piston bowl geometry parameterization and multi-mode optimization. The new code was used to optimize the combustion chamber geometry of a small-bore automotive Diesel engine. The Genetic Algorithm (GA) merit function, which was calculated with a modified version of the KIVA-3V engine simulation code, included NOx, unburned HC, soot, and fuel consumption. A novel parameterization was included in KIVA-GA that allows for a variable number of parameters to define the bowl shape. The in-house G-Smooth grid generation package was used to create the KIVA grids with a specified compression ratio and mesh resolution. The improved KIVA-GA methodology was used to optimize engine emissions and performance simultaneously for two operating conditions.

A computational optimization study is performed for a heavy-duty direct-injection diesel engine using the recently developed KIVA-GA computer code. KIVA-GA performs full cycle engine simulations within the framework of a Genetic Algorithm (GA) global optimization code. Design fitness is determined using a one-dimensional gas -dynamics code for calculation of the gas exchange process, and a three-dimensional CFD code based on KIVA-3V for spray, combustion and emissions formation. The performance of the present Genetic Algorithm is demonstrated using a test problem with a multi-modal analytic function in which the optimum is known a priori. The KIVA-GA methodology is next used to simultaneously investigate the effects of six engine input parameters on emissions and performance for a high speed, medium load operating point for which baseline experimental validation data is available.