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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.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

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.

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.

To model sprays from pressure-swirl atomizers, the connection between the injector and the downstream spray must be considered. A new model for pressure-swirl atomizers is presented which assumes little knowledge of the internal details of the injector, but instead uses available observations of external spray characteristics. First, a correlation for the exit velocity at the injector exit is used to define the liquid film thickness. Next, the film must be modeled as it becomes a thin, liquid sheet and breaks up, forming ligaments and droplets. A linearized instability analysis of the breakup of a viscous, liquid sheet is used as part of the spray boundary condition. The spray angle is estimated from spray photographs and patternator data. A mass averaged spray angle is calculated from the patternator data and used in some of the calculations.