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Metal additive manufacturing has high potential to produce automobile parts, due to its shape flexibility and unique material properties. On the other hand, residual stress which is generated by rapid solidification causes deformation, cracks and failure under building process. To avoid these problems, understanding of internal residual stress distribution is necessary. However, from the view point of measureable area, conventional residual stress measurement methods such as strain gages and X-ray diffractometers, is limited to only the surface layer of the parts. Therefore, neutron which has a high penetration capability was chosen as a probe to measure internal residual stress in this research. By using time of flight neutron diffraction facility VULCAN at Oak Ridge National Laboratory, residual stress for mono-cylinder head, which were made of aluminum alloy, was measured non-distractively. From the result of precise measurement, interior stress distribution was visualized.

An engine-aftertreatment computational model was developed to support in-loop performance simulations of tailpipe emissions and fuel consumption associated with a range of heavy-duty (HD) truck drive cycles. For purposes of this study, the engine-out exhaust dynamics were simulated with a combination of steady-state engine maps and dynamic correction factors that accounted for recent engine operating history. The engine correction factors were approximated as dynamic first-order lags associated with the thermal inertia of the major engine components and the rate at which engine-out exhaust temperature and composition vary as combustion heat is absorbed or lost to the surroundings. The aftertreatment model included catalytic monolith components for diesel exhaust oxidation, particulate filtration, and selective catalytic reduction of nitrogen oxides (NOx) with urea.

Given the importance of the fuel-injection process on the combustion and emissions performance of gasoline direct injected engines, there has been significant recent interest in understanding the fluid dynamics within the injector, particularly around the needle and through the nozzles. The pressure losses and transients that occur in the flow passages above the needle are also of interest. Simulations of these injectors typically use the nominal design geometry, which does not always match the production geometry. Computed tomography (CT) using x-ray and neutron sources can be used to obtain the real geometry from production injectors, but there are trade-offs in using these techniques. X-ray CT provides high resolution, but cannot penetrate through the thicker parts of the injector. Neutron CT has excellent penetrating power but lower resolution.

In this study we identify components of a typical biodiesel fuel and estimate both their individual and mixed thermo-physical and transport properties. We then use the estimated mixture properties in computational simulations to gauge the extent to which combustion is modified when biodiesel is substituted for conventional diesel fuel. Our simulation studies included both conventional diesel combustion (DI) and premixed charge compression ignition (PCCI). Preliminary results indicate that biodiesel ignition is significantly delayed due to slower liquid evaporation, with the effects being more pronounced for DI than PCCI. The lower vapor pressure and higher liquid heat capacity of biodiesel are two key contributors to this slower rate of evaporation. Other physical properties are more similar between the two fuels, and their impacts are not clearly evident in the present study.

The effect of biodiesel content on homogeneous charge compression ignition (HCCI) engine performance has been investigated both experimentally and by computer simulation. Combustion experiments were performed in a single cylinder HCCI engine using blends of soy biodiesel in ultra low sulfur diesel, with concentrations ranging from 0 to 50 vol% and equivalence ratios (Φ) from 0.38 to 0.48. Data from the engine tests included combustion analysis and exhaust composition analysis with standard gaseous emissions equipment. The engine utilized a custom port fuel injection strategy to provide highly premixed charges of fuel and air, making it possible to compare the results with single zone chemical kinetics simulations that were performed using CHEMKIN III, with a reaction set including 670 species and over 3000 reactions.

A detailed component performance, ratings, and cost study was conducted on series and parallel hybrid electric vehicle (HEV) configurations for several battery pack and main electric traction motor voltages while meeting stringent Partnership for a New Generation of Vehicles (PNGV) power delivery requirements. A computer simulation calculated maximum current and voltage for each component as well as power and fuel consumption. These values defined the peak power ratings for each HEV drive system's electric components: batteries, battery cables, boost converter, generator, rectifier, motor, and inverter. To identify a superior configuration or voltage level, life cycle costs were calculated based on the components required to execute simulated drive schedules. These life cycle costs include the initial manufacturing cost of components, fuel cost, and battery replacement cost over the vehicle life.

The heat treatment of steel parts is an essential step in the manufacturing of high-performance components for a variety of commercial and military products. Distortion in the size and shape of parts resulting from the heat treatment process is a pervasive manufacturing problem that causes higher finishing costs, excessive scrap and rework, long delivery times, and negative environmental impact. To date, techniques that have been developed to reduce or eliminate heat treatment distortion are largely based on experience and have been limited to trial and error. This presentation describes the philosophy and results of an ongoing collaborative project to develop a methodology and computer simulation capability to predict ferrous alloy component response (distortion, residual stress, and microstructure) to industrial heat treatment processes for automotive, truck, bearing, and aerospace applications.

The computer-aided-design and analysis of a robust casting process requires the optimization of both mold filling and solidification. A number of commercial casting codes are available for modeling the fluid flow during mold filling and the heat transfer during solidification. The next generation casting process models will build on present capabilities to allow the prediction of microporosity and other defects and microstructure. This paper will discuss the issues involved in the development of next generation casting process models and present results from a computer model for microporosity prediction that is based on first principles, and will take into account alloy composition, alloy microstructure, the initial hydrogen content of the liquid alloy, and the resistance to inter-dendritic fluid flow to feed shrinkage.