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At Boeing’s commercial aircraft production in Everett Washington, the organization that supplies parts to the factory floor (known internally as Company 625) is revising their methods. A new process will deliver parts in kits that correspond to the installation plans used by the mechanics. Several alternative methods are under review. The authors used simulation methods to evaluate and compare these alternatives. This study focuses on the category of parts known as standard fasteners (‘standards’). Through direct observation, interviews with experts, as well as time and motion study, the process flow of the kitting operation was mapped A simulation model was created using the simulation software ARENA to examine two scenarios: the current kitting operation in the factory cribs and the proposed centralization of kitting operation in the Company 625.

Minimizing the stress concentrations around cutouts in a plate is often a design problem, especially in the Aerospace industry. A problem of optimizing spatially varying fiber paths in a symmetric, linear orthotropic composite laminate with a cutout, so as to achieve minimum stress concentration under remote unidirectional tensile loading is of interest in this study. A finite element (FE) model is developed to this extent, which constraints the fiber angles while optimizing the fiber paths, proving essential in manufacturing processes. The idea to be presented could be used to derive fiber paths that would drastically reduce the Stress Concentration Factor (SCF) in a symmetric laminate by using spatially varying fibers in place of unidirectional fibers. The model is proposed for a four layer symmetric laminate, and can be easily reproduced for any number of layers.

This study investigates the use of machine learning methods for the selection of energy storage devices in military electrified vehicles. Powertrain electrification relies on proper selection of energy storage devices, in terms of chemistry, size, energy density, and power density, etc. Military vehicles largely vary in terms of weight, acceleration requirements, operating road environment, mission, etc. This study aims to assist the energy storage device selection for military vehicles using the data-drive approach. We use Machine Learning models to extract relationships between vehicle characteristics and requirements and the corresponding energy storage devices. After the training, the machine learning models can predict the ideal energy storage devices given the target vehicles design parameters as inputs. The predicted ideal energy storage devices can be treated as the initial design and modifications to that are made based on the validation results.

Laser excitation wavelengths for two-line planar laser-induced fluorescence (PLIF) of 3-pentanone have been optimized for simultaneous imaging of temperature and composition under engine-relevant conditions. Validation of the diagnostic was performed in a motored optical IC engine seeded homogeneously with 3-pentanone. PLIF measurements of the uniform mixture during the compression stroke were used to measure the average temperature and to access the random uncertainty in the measurements. To determine the accuracy of the temperature measurements, experimental average temperatures were compared to values computed assuming isentropic compression and to the output of a tuned 1-D engine simulation. The comparison indicated that the absolute accuracy of the temperature measurements is better than ±5%. Probability density functions (PDFs) calculated from the single-shot images were used to estimate the precision of the measurements.

Many experimental efforts to track fuel-air-residual mixture preparation in internal combustion engines have employed laser induced fluorescence (LIF) of tracers. Acetone and 3-pentanone are often chosen as tracers because of their relatively strong LIF signal, weak quenching, and reasonable match to thermo-chemical properties of common fuels such as iso-octane. However, the addition of these tracers to fuel-air mixtures could affect combustion behavior. In this work, we assess these effects to better understand limitations of tracer-based engine measurements. The effects of tracer seeding on combustion phasing, duration, and variation are studied in an HCCI engine using a recompression strategy to accommodate single- and multi-stage-ignition fuels.

Negative valve overlap (NVO) is a valve strategy employed to retain and recompress residual burned gases to assist HCCI combustion, particularly in the difficult regime of low-load operation. NVO allows the retention of large quantities of hot residual burned gases as well as the possibility of fuel addition for combustion control purposes. Reaction of fuel injected during NVO increases charge temperature, but in addition could produce reformed fuel species that may affect main combustion phasing. The strategy holds potential for controlling and extending low-load HCCI combustion. The goal of this work is to demonstrate the feasibility of applying two-wavelength PLIF of 3-pentanone to obtain simultaneous, in-cylinder temperature and composition images during different parts of the HCCI/NVO cycle. Measurements are recorded during the intake and main compression strokes, as well as during the more challenging periods of NVO recompression and re-expansion.

Rational design for fire safety necessarily includes consideration of risk tradeoffs that tend to reduce one risk but may increase another. Traditional engineering design criteria can be supplemented with important factors that rely on expertise from other disciplines. Engineering analysis may be able to address reduction in fire risk due to the introduction of new technology, but may not address the social costs associated with this new technology. For example, the resultant increase in vehicle cost may prevent some people from purchasing a vehicle (impacting individuals' lives), may reduce the number of vehicles sold (impacting manufacturers), and may reduce taxes collected (impacting the government). This must be weighed against decreased risk of property damage, injury, and fatality due to fire. In this paper, the methods of benefit-cost analysis from economics were applied to make this evaluation.

Heat transfer is one of the largest causes of exergy destruction in modern engines. In this paper, exergy distribution modeling was used to determine the potential of reduced engine heat transfer to provide significant gains in engine efficiency. As known from prior work, of itself, reducing heat transfer creates only a small increase in efficiency-most of the exergy is redirected into the exhaust stream-requiring both mechanical and thermal recovery of the exhaust exergy. Mechanical regeneration, through turbocharging and over-expansion, can lead to efficiencies exceeding 50%. Adding thermal regeneration, through high enthalpy steam injection or a bottoming cycle, can increase the efficiency potential to approximately 60%. With implementation of both mechanical and thermal regeneration, the only remaining cause of substantial exergy destruction is the combustion process.

A particle tracking velocimetry (PTV) system has been developed to measure two dimensional velocity fields in a motored axisymmetric engine with a transparent cylinder. The intake flow was seeded with phenolic microballoons (40 μm hollow spheres) and illuminated by a 1 mm thick horizontal sheet of pulsed laser light from a 25 Watt copper vapor laser capable of 30 ns pulses. Photographs containing tracks of dots representing the multiply exposed path of each particle were produced. These images were digitized by a custom scanner capable of 3456 by 5184 pixel resolution and binarized using an iterative threshold routine in order to locate the particles. Software then determined how the individual particles are organized into tracks and presented the results for operator verification. Velocity magnitude and direction were computed for each track and the results were interpolated to a fixed grid for further analysis.

An automotive propulsion concept is presented which utilizes liquid nitrogen as the working fluid for an open Rankine cycle. Ambient heat exchangers are used to power an engine that is configured to maximize heat transfer during the expansion stroke. If sufficient heat input during the expansion process can be realized then this cryogenic propulsive system would provide greater automotive ranges and lower operating costs than those of electric vehicles currently being considered for mass production. The feasibility of meeting this engineering challenge has been evaluated and several means of achieving quasi-isothermal expansion are discussed.

In applications ranging from design of customized vehicle interiors to virtual testing of biomedical devices, the processes of modeling, design and analysis involve the simultaneous treatment of artifacts (i.e., parts designed by humans) and anatomical structures. An inherent conflict arises because the geometric descriptions are completely different. Artifact descriptions are typically the output of computer-aided design (CAD) software and consist of a collection of parametric patches that comprise the boundary of the artifact. In stark contrast, the native description of an anatomical structure typically consists of an image stack obtained using a volumetric scanning technology such as computed tomography (CT) or magnetic resonance imaging (MRI). Current practice for simultaneously dealing with both categories of entities involves working primarily in the world of CAD.

In order to reduce painful and injurious shear stresses for lower limb amputees, prosthetic ankle joints need to provide torsional control in the transverse plane. This paper attempts to characterize biological ankle function in the transverse plane with simple mechanical elements to assist in the design of a biomimetic prosthetic ankle joint. Motion capture data was collected from ten subjects walking in a straight trajectory to model four states of stance phase. Passive elements were chosen to model the ankle in each state. The ankle was observed to act as a quadratic torsional spring in State 1 and as linear torsional springs in States 2, 3 and 4. The results of this study should assist with the mechanical design and control of a biomimetic torsional prosthesis by suggesting a finite state control system and by providing the stiffness coefficients to be controlled for straight walking.

Standard CFD methods require a mesh that fits the boundaries of the computational domain. For a complex geometry the generation of such a grid is time-consuming and often requires modifications to the model geometry. This paper evaluates the Immersed Boundary (IB) approach which does not require a boundary-conforming mesh and thus would speed up the process of the grid generation. In the IB approach the CAD surfaces (in Stereo Lithography -STL- format) are used directly and this eliminates the surface meshing phase and also mitigates the process of the CAD cleanup. A volume mesh, consisting of regular, locally refined, hexahedrals is generated in the computational domain, including inside the body. The cells are then classified as fluid, solid and interface cells using a simple ray-tracing scheme. Interface cells, correspond to regions that are partially fluid and are intersected by the boundary surfaces.

Computational fluid dynamic (CFD) simulations that include realistic combustion/emissions chemistry hold the promise of significantly shortening the development time for advanced high-efficiency, low-emission engines. However, significant challenges must be overcome to realize this potential. This paper discusses these challenges in the context of diesel combustion and outlines a technical program based on the use of surrogate fuels that sufficiently emulate the chemical complexity inherent in conventional diesel fuel.

The development of surrogate mixtures that represent gasoline combustion behavior is reviewed. Combustion chemistry behavioral targets that a surrogate should accurately reproduce, particularly for emulating homogeneous charge compression ignition (HCCI) operation, are carefully identified. Both short and long term research needs to support development of more robust surrogate fuel compositions are described. Candidate component species are identified and the status of present chemical kinetic models for these components and their interactions are discussed. Recommendations are made for the initial components to be included in gasoline surrogates for near term development. Components that can be added to refine predictions and to include additional behavioral targets are identified as well. Thermodynamic, thermochemical and transport properties that require further investigation are discussed.

Map matching determines which road a vehicle is on based on inaccurate measured locations, such as GPS points. Simple algorithms, such as nearest road matching, fail often. We introduce a new algorithm that finds a sequence of road segments which simultaneously match the measured locations and which are traversable in the time intervals associated with the measurements. The time constraint, implemented with a hidden Markov model, greatly reduces the errors made by nearest road matching. We trained and tested the new algorithm on data taken from a large pool of real drivers.

This investigation of the use of cryogens as energy storage media for zero emission vehicles has found that using liquid nitrogen to liquefy the working fluids of one or more closed Rankine power cycles can be an effective means for increasing motive power. System configurations are presented which can realize over 50% of the availability of liquid nitrogen without relying on isothermal expanders. A zero emission vehicle utilizing such a propulsion system would have an energy storage reservoir that can be refilled in a matter of minutes and a range comparable to that of a conventional automobile.

Strict NOx and soot emission regulations for Diesel engines have created an interest in low-temperature partially-homogeneous combustion regimes in both the US and Europe. One strategy, Homogeneous-Charge Late-Injection (HCLI) combustion utilizes 55% or more cooled external Exhaust Gas Recirculation (EGR) with a single Direct Injection strategy to control ignition timing. These engines are operated at low temperatures to ensure near zero NOx emissions, implying that fuel in the thermal boundary layers will not reach sufficient temperature to fully oxidize, resulting in Unburnt Hydrocarbon (UHC) and CO emissions. Of particular interest to HCLI engines are the UHC's that are not fully oxidized by the Diesel Oxidation Catalyst (DOC). Experimental measurements reveal that at average equivalence ratios greater than 0.8, methane is the single largest tailpipe-out UHC emission.

In-cylinder pre-processing (or recompression reaction) of direct-injected fuel during the negative valve overlap period of a retention-strategy HCCI engine is investigated for extension of the low-load limit of operation. Experimental studies of three variables (compression ratio, pilot injection timing, and pilot injection amount) were conducted in order to optimize the effects of recompression reaction by changing the sensible and chemical energy environment during recompression. The results from compression ratio variation show that there exist optimum values of equivalence ratio and extent of recompression reaction, which expand the low-load operating region. The pilot injection timing variation demonstrates good controllability of the extent of recompression reaction by effectively changing the in-cylinder residence time of the pilot-injected fuel.

This paper develops and tests algorithms for predicting the end-to-end route of a vehicle based on GPS observations of the vehicle's past trips. We show that a large portion a typical driver's trips are repeated. Our algorithms exploit this fact for prediction by matching the first part of a driver's current trip with one of the set of previously observed trips. Rather than predicting upcoming road segments, our focus is on making long term predictions of the route. We evaluate our algorithms using a large corpus of real world GPS driving data acquired from observing over 250 drivers for an average of 15.1 days per subject. Our results show how often and how accurately we can predict a driver's route as a function of the distance already driven.