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The study of spray-wall interaction is of great importance to understand the dynamics during fuel-surface impingement process in modern internal combustion engines. The identification of droplet post-impingement pattern (contact, transition, non-contact) and droplet characteristics can quantitatively provide an estimation of energy transfer for spray-wall interaction, thus further influencing air-fuel mixing and emissions under combusting conditions. Theoretical criteria of single droplet post-impingement pattern on a dry wall have been experimentally and numerically studied by many researchers to quantify the hydrodynamic droplet behaviors. However, apart from model fidelity, another issue is the scalability. A theoretical criterion developed from one case might not be well suited to another scenario. In this paper, a data-driven approach for single droplet-dry wall post-impingement pattern utilizing arithmetical machine learning classification methods is proposed and demonstrated.

Off road navigation demands ground robots to traverse complex and often changing terrain. Classification and assessment of terrain can improve path planning strategies by reducing travel time and energy consumption. In this paper we introduce a terrain classification and assessment framework that relies on both exteroceptive and proprioceptive sensor modalities. The robot captures an image of the terrain it is about to traverse and records corresponding vibration data during traversal. These images are manually labelled and used to train a support vector machine (SVM) in an offline training phase. Images have been captured under different lighting conditions and across multiple locations to achieve diversity and robustness to the model. Acceleration data is used to calculate statistical features that capture the roughness of the terrain whereas angular velocities are used to calculate roll and pitch angles experienced by the robot.

The proliferation of small silicon micro-chips has led to a large assortment of low-cost transducers for data acquisition. Production vehicles on average exploit more than 60 on board sensors, and that number is projected to increase beyond 200 per vehicle by 2020. Such a large increase in sensors is leading the fourth industrial revolution of connectivity and autonomy. One major downfall to installing many sensors is compromises in their accuracy and processing power due to cost limitations for high volume production. The same common errors in data acquisition such as sampling, quantization, and multiplexing on the CAN bus must be accounted for when utilizing an entire array of vehicle sensors. A huge advantage of onboard sensors is the ability to calculate vehicle parameters during a daily drive cycle to update ECU calibration factors in real time. One such parameter is driveline damping, which changes with gear state and drive mode. A damping value is desired for every gear state.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

At the onset of soak, air and surface temperatures in an engine bay enclosure are elevated since temperature of heat sources are high while convective cooling is sharply reduced as a result of airflow being shut off from the inlet grilles of the vehicle leading to temperature spikes. Accurate simulation of this important thermal and flow regime that is natural convection driven, highly transient and complex is therefore very important. In this investigation, we simulate flow in the engine bay at the onset of soak with fixed thermal boundary conditions where the geometries representing the engine bay and components are simplified. Good agreement was observed with detailed experimental data available in references for both velocities and temperatures.

Increasing fuel injection pressure has enabled reduction of diesel emissions while retaining the advantage of the high thermal efficiency of diesel engines. With production diesel injectors operating in the range from 300 to 2400 bar, there is interest in injection pressures of 3000 bar and higher for further emissions reduction and fuel efficiency improvements. Fundamental understanding of diesel spray characteristics including very early injection and non-vaporizing spray penetration is essential to improve model development and facilitate the integration of advanced injection systems with elevated injection pressure into future diesel engines. Studies were conducted in an optically accessible constant volume combustion vessel under non-vaporizing conditions. Two advanced high pressure multi-hole injectors were used with different hole diameters, number of holes, and flow rates, with only one plume of each injector being imaged to enable high frame rate imaging.

The U.S. Renewable Fuel Standard (RFS2) requires an increase in the use of advanced biofuels up to 36 billion gallons by 2022. Longer chain alcohols, in addition to cellulosic ethanol and synthetic biofuels, could be used to meet this demand while adhering to the RFS2 corn-based ethanol limitation. Higher carbon number alcohols can be utilized to improve the energy content, knock resistance, and/or petroleum displacement of gasoline-alcohol blends compared to traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part I of this paper focuses on the development of scenarios by which to compare higher alcohol fuel blends to traditional ethanol blends. It also details the implementation of fuel property prediction methods adapted from literature. Possible combinations of eight alcohols mixed with a gasoline blendstock were calculated and the properties of the theoretical fuel blends were predicted.

Long duration human space missions, as planned in the Vision for Space Exploration, will not be possible without applying unprecedented levels of automation to support the human endeavors. The automated and robotic systems must carry the load of routine “housekeeping” for the new generation of explorers, as well as assist their exploration science and engineering work with new precision. Fortunately, the state of automated and robotic systems is sophisticated and sturdy enough to do this work — but the systems themselves have never been human-rated as all other NASA physical systems used in human space flight have. Our intent in this paper is to provide perspective on requirements and architecture for the interfaces and interactions between human beings and the astonishing array of automated systems; and the approach we believe necessary to create human-rated systems and implement them in the space program.

This paper discusses the problem of obtaining electric machines (EM) for advanced electric drives (AED) used in more electric architecture (MEA) applicable to aircraft, spacecraft, and military ground vehicles. The AED are analyzed by those aspects of Six Sigma theory that relate to critical-to-quality (CTQ) subjects. Using this approach, weight, volume, reliability, efficiency, and cost CTQ are addressed to develop a balance among them, resulting in an optimized system. The influence of machine controllers and system considerations is discussed. As a part of the machine evaluation process, speeds, bearings, complexities, rotor mechanical and thermal limitations, torque pulsations, currents, and power densities are considered. A methodology for electric machine selection is demonstrated. An example of high-speed, high-performance machine application is shown. A system approach is used for overall electric machine selection and optimization.

Model-based control strategies are important for meeting the dual objective of maximizing NOx reduction and minimizing NH3 slip in urea-SCR catalysts. To be implementable on the vehicle, the models should capture the essential behavior of the system, while not being computationally intensive. This paper discusses the adequacy of two different reduced order SCR catalyst models and compares their performance with a higher order model. The higher order model assumes that the catalyst has both diffusion and reaction kinetics, whereas the reduced order models contain only reaction kinetics. After describing each model, its parameter identification and model validation based on experiments on a Navistar I6 7.6L engine are presented. The adequacy of reduced order models is demonstrated by comparing the NO, NO2 and NH3 concentrations predicted by the models to their concentrations from the test data.

Rear Window Buffeting (RWB) is the low-frequency, high amplitude, sound that occurs in many 4-door vehicles when driven 30-70 mph with one rear window lowered. The goal of this paper is to demonstrate that the mechanisms of RWB are similar to that of sun roof buffeting and to describe the results of several actions suspected in contributing to the severity of RWB. Finally, the results of several experiments are discussed that may lend insight into ways to reduce the severity of this event. A detailed examination of the side airflow patterns of a small Sport Utility Vehicle (SUV) shows these criteria exist on a small SUV, and experiments to modify the SUV airflow pattern to reduce RWB are performed with varying degrees of success. Based on the results of these experiments, design actions are recommended that may result in the reduction of RWB.

Engineering education at the University level is enhanced by competition-based projects. The SAE Clean Snowmobile Challenge is a prime example of how competition-based engineering education benefits the small engines industry and improves the engineering talent pool of the nation in general. For the past several decades, SAE has encouraged young engineers to compete in designing off road vehicles (Baja SAE ®), small race cars (Formula SAE ®), remote control airplanes (Aero Design ®), high mileage vehicles (Supermileage ®) and robots (Walking Robot ®). Now a new competition, the SAE Clean Snowmobile Challenge ™ (CSC), based on designing a cleaner and quieter snowmobile has led to a new path for young engineers to explore the challenges of designing engines that emit less pollution and noise. The paper will summarize the results of the most recent Clean Snowmobile Challenge 2006 and document the successes of the past seven years of the Challenge.

The Water Processor Assembly (WPA) for use on the International Space Station (ISS) includes various technologies for the treatment of waste water. These technologies include filtration, ion exchange, adsorption, catalytic oxidation, and iodination. The WPA hardware implementing portions of these technologies, including the Particulate Filter, Multifiltration Bed, Ion Exchange Bed, and Microbial Check Valve, was recently qualified for chemical performance at the Marshall Space Flight Center. Waste water representing the quality of that produced on the ISS was generated by test subjects and processed by the WPA. Water quality analysis and instrumentation data was acquired throughout the test to monitor hardware performance. This paper documents operation of the test and the assessment of the hardware performance.

A trade study conducted in 2001 selected a rotary disk separator as the best candidate to meet the requirements for an International Space Station (ISS) Carbon Dioxide Reduction Assembly (CRA). The selected technology must provide micro-gravity gas/liquid separation and pump the liquid from 69 kPa (10 psia) at the gas/liquid interface to 124 kPa (18 psia) at the wastewater bus storage tank. The rotary disk concept, which has pedigree in other systems currently being built for installation on the ISS, failed to achieve the required pumping head within the allotted power. The separator discussed in this paper is a new design that was tested to determine compliance with performance requirements in the CRA. The drum separator and pump (DSP) design is similar to the Oxygen Generator Assembly (OGA) Rotary Separator Accumulator (RSA) in that it has a rotating assembly inside a stationary housing driven by a integral internal motor[1].

Heavy-duty diesel engine particulate matter (PM) emissions must be reduced from 0.1 to 0.01 grams per brake horsepower-hour by 2007 due to EPA regulations [1]. A catalyzed particulate filter (CPF) is used to capture PM in the exhaust stream, but as PM accumulates in the CPF, exhaust flow is restricted resulting in reduced horsepower and increased fuel consumption. PM must therefore be burned off, referred to as CPF regeneration. Unfortunately, nominal exhaust temperatures are not always high enough to cause stable self-regeneration when needed. One promising method for active CPF regeneration is to inject fuel into the exhaust stream upstream of an oxidation catalytic converter (OCC). The chemical energy released during the oxidation of the fuel in the OCC raises the exhaust temperature and allows regeneration.

The Internal Thermal Control System (ITCS) has been developed jointly by Boeing Corporation, Huntsville, Alabama and Honeywell Engines & Systems, Torrance, California to meet the internal thermal control needs for the International Space Station (ISS). The ITCS provides heat removal for the critical life support systems and thermal conditioning for numerous experiment racks. The ITCS will be fitted on a number of modules on the ISS. The first US Element containing the ITCS, Node 1, was launched in December 1998. Since Node 1 does not contain a pump to circulate the fluid it was not filled with ITCS fluid until after the US Laboratory Module was installed. The second US Element module, US Laboratory Module, which contains the pumps and all the major ITCS control hardware, was launched in February 2001. The third US Element containing the ITCS, the US Airlock, was launched in July 2001.

An important aspect of air revitalization for life support in spacecraft is the removal of carbon dioxide from cabin air. Several types of carbon dioxide removal systems are in use in spacecraft life support. These systems rely on various removal techniques that employ different architectures and media for scrubbing CO2, such as permeable membranes, liquid amine, adsorbents, and absorbents. Sorbent systems have been used since the first manned missions. The current state of key technology is the existing International Space Station (ISS) Carbon Dioxide Removal Assembly (CDRA), a system that selectively removes carbon dioxide from the cabin atmosphere. The CDRA system was launched aboard UF-2 in February 2001 and resides in the U.S. Destiny Laboratory module. During the past three years, the CDRA system has operated with varying degrees of success.

The mechanical performance of injection molded glass-fiber reinforced plastic parts is highly anisotropic and depends strongly on the kinetics (orientation and distribution) of the glass-fiber and the part geometry. Similarly, the bulk and local mechanical performance at the ribs, walls and welds is influenced by these glass-fibers and the specific processing technology (including joining) used, as related to melt-flow and melt-pool formation and glass-fiber re-orientation. The purpose of this study is to show: the effect of short glass-fiber orientation at the pre-welded beads, ribs and wall areas for injection molded and subsequently welded parts the short-term mechanical performance of welded butt-joints that have various geometry and thickness, namely “straight” and “T-type” welds.

In response to consumer demand, automakers are adding more safety, security, and convenience features to vehicle access control systems. Also, in a continuing effort to be more profitable, automakers are reducing costs by outsourcing the design of systems/sub-systems/components, reducing their supply base, and minimizing part numbers by sharing components across several platforms. In an attempt to improve efficiency and productivity, many OEM's have adopted a “corporate latch” strategy, implementing the same latch across several manufacturing platforms and marketing divisions. Honeywell's revolutionary door latch design efficiently and cost effectively addresses vehicle OEMs' current and future requirements for performance and functionality.

A three-year program to develop a Direct Drive Hall Effect Thruster (D2HET) system began 15 months ago as part of the NASA Advanced Cross-Enterprise Technology Development initiative. The system is expected to reduce significantly the power processing, complexity, weight, and cost over conventional low-voltage systems. The D2HET will employ solar arrays that operate at voltages greater than 300V, and will be an enabling technology for affordable planetary exploration. It will also be a stepping-stone in the production of the next generation of power systems for Earth orbiting satellites. This paper provides a general overview of the program and reports the first year's findings from both theoretical and experimental components of the program.