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Integrating the seemingly divergent objectives of aircraft seat configuration is a difficult task. Aircraft manufacturers look to design seats to maximize customer satisfaction and in-flight safety, but these objectives can conflict with the profit motive of airline companies. In order to boost revenue by increasing the number of passengers per aircraft, airline companies may increase seat height and decrease seat pitch. This results in disaccommodation of a greater percentage of the passenger population and is a reason for rising customer dissatisfaction. This paper describes an effort to bridge this gap by incorporating digital human models, layout optimization, and a profit-maximizing constraint into the aircraft seat design problem. A simplified aircraft seat design experiment is conceptualized and its results are extrapolated to an airline passenger population.

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.

Considerable improvements can be obtained in battery performance for hybrid electric vehicles (HEVs) by employing an electrochemistry-transport model based on a multi-physics modeling framework and ultrafast numerical algorithms. One important advantage of this approach over the lumped equivalent circuit (or look-up table) approach is the ability of the former to adapt to changes in design and control. In this work, we present mathematical and numerical details of our approach, and demonstrate the robustness of this battery model in simulation of short-pulse charge/discharge characteristic of HEV driving cycles under room and low temperatures.

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.

Ongoing efforts in applying a “high-end” turbulent combustion model (a transported probability density function - tPDF - method) to direct-injection internal combustion engines are discussed. New numerical algorithm and physical modeling issues arise compared to more conventional modeling approaches. These include coupling between Eulerian finite-volume methods and Lagrangian Monte Carlo particle methods, liquid fuel spray/tPDF coupling, and heat transfer. Sensitivity studies are performed and quantitative comparisons are made between model results and experimental measurements in a diesel/PCCI engine. Marked differences are found between tPDF results that account explicitly for turbulence/chemistry interactions (TCI) and results obtained using models that do not account for TCI. Computed pressure and heat release profiles agree well with experimental measurements and respond correctly to variations in engine operating conditions.

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.

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.

The Pennsylvania State University Advanced Vehicle Team (PSU AVT) is one of the fifteen (15) participating teams at the EcoCAR 2 “Plugging In to the Future” challenge. The team has worked in the design, development and validation of converting a 2013 Chevrolet Malibu, into an advanced technology hybrid vehicle. The PSU AVT has determined that a Plug-In Series Electric Hybrid architecture best meets the design goals of the EcoCAR 2 competition. The vehicle will utilize a front-wheel drivetrain powered by a Magna E-drive; an Auxiliary Power Unit (APU) based on a naturally aspirated Weber MPE 750 engine, converted for use with E85, coupled to a UQM PowerPhase 75 generator; an Energy Storage System (ESS) based on six A123, 15s3p battery modules; and a Mototron ECM-5554-112-0904 controller as the Master Vehicle Controller (MVC).

Polymer Electrolyte Membrane Fuel Cell (PEMFC) is regarded as a potential alternative clean energy source for automobile applications. Key challenges to the acceptance of PEMFC for automobiles are the cost reduction, improvement in power density for its compactness, and cold-start capability. High current density operation is a promising solution for them. However, high current density operation under normal and sub-zero temperature requires more oxygen flux for the electrochemical reaction in the catalyst layer, and it causes more heat and water flux, resulting in the significant voltage losses. So, the theoretical investigation is very helpful for the fundamental understanding of complex transport phenomena in high current density operation under normal and sub-zero temperature. In this study, the numerical model was established to elucidate the impacts of mass transport phenomena on the cell performance through the numerical validation with experimental and visualization results.

A study has been experimentally conducted in an optically-accessible DI Diesel engine operating on 50/50 mixture of iso-octane and tetradecane to evaluate a planar laser light scattering technique for the in-cylinder study of soot. Two simultaneous images, taken with vertically and horizontally polarized scattered light, were used to determine the polarization ratio, CHH/CW. This magnitude of the polarization ratio was employed to distinguish soot particles from fuel droplets. The spatial and temporal variations of soot during the combustion cycle were investigated with images taken at various crank angles and swirl levels at three different planes in the combustion bowl. For the high swirl case, soot was uniformly distributed in the combustion bowl. For the non-swirl case, however, soot was mainly observed near the wall and at the top plane, and was observed to exist later into the expansion stroke.

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.

Standing reach envelopes are important tools for the design of industrial and vehicle environments. Previous work in this area has focussed on manikin-based (where a few manikins are used to simulate individuals reaching within the region of interest) and population-based (where data are gathered on many individuals reaching in a constrained environment) approaches. Each of these methods has merits and shortfalls. The current work bridges the manikin- and population-based approaches to assessing reach by creating population models using kinematic simulation techniques driven by anthropometric data. The approach takes into account body dimensions, balance, and postural cost to create continuous models that can be used to assess designs with respect to both maximal and submaximal reaches. Cost is quantified as the degree to which the torso is involved in the reach, since the inclination of the torso is a good measure of lower-back load and may be related to subjective reach difficulty.

An experimental study was conducted to determine if an organic fuel additive could reduce engine out hydrocarbon and NOx emissions. A production four cylinder spark ignited engine with throttle body fuel injection was used for the study. A full boiling range base fuel, an additized base fuel, a base fuel with methyl tertiary butyl ether (MTBE) and a base fuel with MTBE and additive were used in the engine tests. Additive concentration was 1/2% by mass. Hydrocarbon and NOx measurements were recorded for 11 load/speed conditions. Hydrocarbon speciation data was taken at two of these conditions. The data from the experiments was analyzed in a pair-wise fashion for the fuels with and without the additive to determine whether statistically significant changes occurred.

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.

Thermodynamics is the key component of materials science and engineering. The manifestation of thermodynamics is typically represented by phase diagrams, traditionally for binary and occasionally ternary systems. Consequently, the applications of thermodynamics have been rather limited in multi-component engineering materials. Computational thermodynamics, developed in the last few decades, has released the power of thermodynamics. In this presentation, fundamental thermodynamics is reviewed, followed by an introduction of computational thermodynamics in terms of first-principles calculations and thermodynamic modeling, and its application to Mg alloys.

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.

Designing for human variability (DfHV) requires efficient allocation of sizing and adjustability. This can preserve product performance while reducing some measures of cost. For example, specifying only as much adjustability as necessary for a desired level of accommodation leads to devices which are better suited to their users and more cost efficient. Similarly, when multiple sizes of an adjustable artifact are to be produced, specifying only as many sizes as are necessary, with an appropriate amount of adjustability per size, leads to a set of products that cost less, require fewer unique parts, facilitate maintenance standardization, and ease inventory control. An alternative to the standard procedure of evenly dividing size ranges is considered wherein an equal degree of accommodation per size is also presented. A simple example related to exercise bicycle seat height is discussed.