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The effects of imaging system resolution and laser sheet thickness on the measurement of the Batchelor scale were investigated in a single-cylinder optical engine. The Batchelor scale was determined by fitting a model spectrum to the dissipation spectrum that was obtained from fuel tracer planar laser-induced fluorescence (PLIF) images of the in-cylinder scalar field. The imaging system resolution was quantified by measuring the step-response function; the scanning knife edge technique was used to measure the 10-90% clip width of the laser sheet. In these experiments, the spatial resolution varied from a native resolution of 32.0 μm to 137.4 μm, and the laser sheet thickness ranged from 108 μm to 707 μm. Thus, the overall resolution of the imaging system was made to vary by approximately a factor of four in the in-plane dimension and a factor of six in the out-of-plane dimension.

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.

The University of Wisconsin-Madison Snowmobile Team has designed and constructed a clean, quiet, high performance snowmobile for entry in the 2008 Society of Automotive Engineers' Clean Snowmobile Challenge. Built on a 2003 cross-country touring chassis, this machine features a 750 cc fuel-injected four-stroke engine equipped with a fuel sensor which allows operation ranging from regular gasoline to an 85% blend of ethanol and gasoline (E85). The engine has been customized with a Mototron control system which allows for full engine optimization using a range of fuels from E00 to E85. Utilizing a heated oxygen sensor and a 3-way catalyst customized for this engine by W.C. Heraeus-GmbH, this sled reduces NOx, HC and CO emissions by up to 89% to an average specific mass of 0.484, 0.154, 4.94 g/kW-hr respectively. Finally, the Mototron system also allowed Wisconsin to extract another 4 kW from the Weber 750cc engine; producing 45 kW and 65 Nm of torque.

The CFD tools in aerodynamic design process have been commonly used in aerospace industry in last three decades. Although there are many CFD software algorithms developed for aerodynamic applications, the nature of a complex, three-dimensional geometry in incompressible highly separated, viscous flow made computational simulation of ground vehicle aerodynamics more difficult than aerospace applications. However, recent developments in computational hardware and software industry enabled many new engineering applications on computational environment. Traditional production process has largely influenced by computational design, analysis, manufacturing and visualization. Different aspects of linking advanced computational tools and aerodynamic vehicle design challenges are discussed in the present work. Key technologies like parallel computation, turbulence modeling and CFD/wind tunnel compatibility issues are presented.

In-cylinder blending of gasoline and diesel to achieve Reactivity Controlled Compression Ignition (RCCI) has been shown to reduce NOX and particulate matter (PM) emissions while maintaining or improving brake thermal efficiency as compared to conventional diesel combustion (CDC). The RCCI concept has an advantage over many advanced combustion strategies in that the fuel reactivity can be tailored to the engine speed and load allowing stable low-temperature combustion to be extended over more of the light-duty drive cycle load range. Varying the premixed gasoline fraction changes the fuel reactivity stratification in the cylinder providing further control of combustion phasing and pressure rise rate than the use of EGR alone. This added control over the combustion process has been shown to allow rapid engine operating point exploration without direct modeling guidance.

A NEW electronic circuit arrangement added to the electro-optical pyrometer developed at the University of Wisconsin indicates instantaneously the temperature in the combustion chamber of a diesel engine. The electronic device, which is described in this paper, solves an equation relating true temperature to intensity and wave length of monochromatic radiation from a luminous flame. True flame temperature is charted on an oscillograph as a function of such abscissas as time or crank angle. Several circuits are reviewed which were found unsuited for use with the pyrometer but which may be useful for other applications.

This paper reports the mass-burning rate in a rotary combustion engine. The mass-burning rate is calculated through an iterative constituent and energy constraints during the combustion process. First approximation is obtained through the firing and motoring-pressure trace as recorded by an image-retaining oscilloscope and recorded subsequently by a polaroid camera. Effect of engine load, engine speed, relative (A/F) on the mass-burning rate and maximum heat release rate were studied. Three different type of fuels were used in the experimental test runs.

To meet future world energy demands, the engineer’s task will be to develop, through research, means of supplying new sources of energy. Though nuclear processes and solar energy will provide future energy, they are not readily adaptable to portable power systems due to inherent shortcomings. Energy can be supplied to portable power systems by energy storage systems using chemical, mechanical, or electrical forms, or it may be supplied through energy-in-transit systems. Technical discussion of various systems is presented. To develop suitable energy storage systems, thought must be given to problems of construction, operation, maintenance, and economics. Research is necessary to determine which chemical fuels are most adaptable for internal combustion engines.

The infrared radiation method of compression and end-gas temperature measurement was applied to the problem of measuring gas temperatures up to the time of knock. Pressure data were taken for each run on a CFR engine with mixtures of isooctane and n-heptane under both knocking and nonknocking conditions. Main engine parameters studied were the intake pressure, intake temperature, and engine speed. The rate and extent of chemical energy release were calculated from the temperature and pressure histories using an energy balance. The computed rates of chemical energy release were correlated to a chain-type kinetic model

The development of a high speed, multichannel data acquisition system is described. A precision magnetic tape recorder is used to record analog data from highly transient phenomena. Analog-to-digital data conversion is performed on a hybrid computer and the digitized data is processed using large, high speed digital computers. A detailed example of the application of the system to the measurement of rates-of-injection, rates-of-heat release, and instantaneous rates-of-heat transfer from the cylinder gases to the cylinder walls in a high speed open-chamber diesel engine is presented.

The EcoCAR Mobility Challenge (EMC) is the latest edition of the Advanced Vehicle Technology Competition (AVTC) series sponsored by the US Department of Energy. This competition challenges 11 North American universities to redesign a stock 2019 Chevrolet Blazer into an energy-efficient, SAE level 2-autonomous mild hybrid electric vehicle (mHEV) for use in the Mobility as a Service (MaaS) market. The Mississippi State University (MSU) team designed a P4 electric powertrain with an 85kW (113.99 HP) permanent magnet synchronous machine (PMSM) powered by a custom 5.4 kWh lithium-ion energy storage system. To maximize energy efficiency, Model Based Design concepts were leveraged to optimize the overall gear ratio for the P4 system. To accommodate this optimized ratio in the stock vehicle, a custom offset gearbox was designed that links the PMSM to the rear drive module.

Sector mesh modeling is the dominant computational approach for combustion system design optimization. The aim of this work is to quantify the errors descending from the sector mesh approach through three geometric modeling approaches to an optical diesel engine. A full engine geometry mesh is created, including valves and intake and exhaust ports and runners, and a full-cycle flow simulation is performed until fired TDC. Next, an axisymmetric sector cylinder mesh is initialized with homogeneous bulk in-cylinder initial conditions initialized from the full-cycle simulation. Finally, a 360-degree azimuthal mesh of the cylinder is initialized with flow and thermodynamics fields at IVC mapped from the full engine geometry using a conservative interpolation approach. A study of the in-cylinder flow features until TDC showed that the geometric features on the cylinder head (valve tilt and protrusion into the combustion chamber, valve recesses) have a large impact on flow complexity.

The long-term goal of this work is to develop a conceptual model for multiple injections of diesel jets. The current work contributes to that effort by performing a detailed modeling investigation into mechanisms that are predicted to control 1st and 2nd stage ignition in single-pulse diesel (n-dodecane) jets under different conditions. One condition produces a jet with negative ignition dwell that is dominated by mixing-controlled heat release, and the other, a jet with positive ignition dwell and dominated by premixed heat release. During 1st stage ignition, fuel is predicted to burn similarly under both conditions; far upstream, gases at the radial-edge of the jet, where gas temperatures are hotter, partially react and reactions continue as gases flow downstream. Once beyond the point of complete fuel evaporation, near-axis gases are no longer cooled by the evaporation process and 1st stage ignition transitions to 2nd stage ignition.

In the current work, a series-hybrid vehicle has been constructed that utilizes a dual-fuel, Reactivity Controlled Compression Ignition (RCCI) engine. The vehicle is a 2009 Saturn Vue chassis and a 1.9L turbo-diesel engine converted to operate with low temperature RCCI combustion. The engine is coupled to a 90 kW AC motor, acting as an electrical generator to charge a 14.1 kW-hr lithium-ion traction battery pack, which powers the rear wheels by a 75 kW drive motor. Full vehicle testing was conducted on chassis dynamometers at the Vehicle Emissions Research Laboratory at Ford Motor Company and at the Vehicle Research Laboratory at Oak Ridge National Laboratory. For this work, the US Environmental Protection Agency Highway Fuel Economy Test was performed using commercially available gasoline and ultra-low sulfur diesel. Fuel economy and emissions data were recorded over the specified test cycle and calculated based on the fuel properties and the high-voltage battery energy usage.

Distracted driving remains a serious risk to motorists in the US and worldwide. Over 3,000 people were killed in 2013 in the US because of distracted driving; and over 420,000 people were injured. A system that can accurately detect distracted driving would potentially be able to alert drivers, bringing their attention back to the primary driving task and potentially saving lives. This paper documents an effort to develop an algorithm that can detect visual distraction using vehicle-based sensor signals such as steering wheel inputs and lane position. Additionally, the vehicle-based algorithm is compared with a version that includes driving-based signals in the form of head tracking data. The algorithms were developed using machine learning techniques and combine a Random Forest model for instantaneous detection with a Hidden Markov model for time series predictions.