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This paper attempts to assess the benefits of a unique distributed propulsion concept, known as the Multi-Gas Generator Fan (MGGF) system, over conventional turbofan engines on civilian vertical takeoff and landing (VTOL) applications. The MGGF-based system has shown the potential to address the fundamental technical challenge in designing a VTOL aircraft: the significant mismatch between the power requirements at lift-off/hover and cruise. Vehicle-level performance and sizing studies were implemented using the Grumman Design 698 tilt-nacelle V/STOL aircraft as a notional personal air vehicle (PAV), subjected to hypothetical single engine failure (SEF) emergency landing requirements and PAV mission requirements.

As gas prices and climate change become the preeminent issues of today, more research effort is being directed towards the development of cheaper and cleaner alternative energy sources. These efforts have been further complemented with research into the applicability of these sources to air, land and sea borne vehicles. In this report a notional C-172R general aviation aircraft is retrofitted with a PEM power plant as a case-study. Lower bounds for useful load and range are set in such a way that the results can be useful in determining how much improvement in the technology would be required to power a useful general aviation vehicle. It is seen that even at the predicted 2015 fuel cell technology level (per US Department of Energy projections), PEM systems would still be infeasible for this vehicle due to low specific power. Further investigation revealed that a PEM-battery hybrid system had better chances of feasibility.

A fuel cell which uses pure hydrogen sulfide as fuel and a solid electrolyte of ceria stabilized with yttria (YSC) has been proposed, with the configuration H2S, Pt/YSC/Pt, O2 (air), operating at temperatures of 600 to 800° C. Initial experiments will use platinum electrodes, with subsequent runs using various perovskite type electrodes. The YSC electrolye system exhibits better ionic conductivity than the more familiar YSZ electrolytes, and thus the fuel cell will operate at a lower temperature range. Cell component manufacture, cell experiments, and analytical techniques are discussed.

The recent development of electric vehicles creates a new area of interest regarding their potential impacts on natural resource and energy networks. Water consumption is of particular interest, as water scarcity becomes a growing problem in many regions of the world. Water usage can be traced to the production of gasoline, as well as electricity, for regular operation of these vehicles. This paper focuses on the development of a framework to analyze the amount of water consumed in the operation of both conventional and electric vehicles. Using the Systems Modeling Language, a model was developed based on the water consumed directly in energy generation and processing as well as water consumed in obtaining and processing a vehicle's fuels. This model and framework will use the above water consumption breakdown to examine conventional and electric vehicles in metropolitan Atlanta to assess their impacts on that and other urban networks.

Spray processes, such as primary breakup, play an important role for subsequent combustion processes and emissions formation. Accurate modeling of these spray physics is therefore key to ensure faithful representation of both the global and local characteristics of the spray. However, the governing physical mechanisms underlying primary breakup in fuel sprays are still not known. Several theories have been proposed and incorporated into different engineering models for the primary breakup of fuel sprays, with the most widely employed models following an approach based on aerodynamically-induced breakup, or more recently, based on liquid turbulence-induced breakup. However, a complete validation of these breakup models and theories is lacking since no existing measurements have yielded the joint liquid mass and drop size distribution needed to fully define the spray, especially in the near-nozzle region.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.

This paper looks at a method for decomposing a manufactured product into what is called an “activity space.” The method uses an activity based costing scheme to structure the model and organize the information. It is discussed how the activity space is used to perform sustainability assessments of a manufactured product and the manufacturing process from different viewpoints and perspectives. The way in which the activity space is used to perform an assessment from several viewpoints is discussed.

Compressed natural gas (CNG) is an attractive, alternative fuel for spark-ignited (SI), internal combustion (IC) engines due to its high octane rating, and low energy-specific CO2 emissions compared with gasoline. Directly-injected (DI) CNG in SI engines has the potential to dramatically decrease vehicles’ carbon emissions; however, optimization of DI CNG fueling systems requires a thorough understanding of the behavior of CNG jets in an engine environment. This paper therefore presents an experimental and modeling study of DI gaseous jets, using methane as a surrogate for CNG. Experiments are conducted in a non-reacting, constant volume chamber (CVC) using prototype injector hardware at conditions relevant to modern DI engines. The schlieren imaging technique is employed to investigate how the extent of methane jets is impacted by changing thermodynamic conditions in the fuel rail and chamber.

This paper presents a comparative analysis of two different power-split hybrid-electric vehicle (HEV) powertrains using backward-looking simulations. Compared are the front-wheel drive (FWD) Toyota Hybrid System II (THS-II) and the FWD General Motors Allison Hybrid System II (GM AHS-II). The Toyota system employs a one-mode electrically variable transmission (EVT), while the GM system employs a two-mode EVT. Both powertrains are modeled with the same assumed mid-size sedan chassis parameters. Each design employs their native internal combustion (IC) engine because the transmission's characteristic ratios are designed for the respective brake specific fuel consumption (BSFC) maps. Due to the similarities (e.g., power, torque, displacement, and thermal efficiency) between the two IC engines, their fuel consumption and performance differences are neglected in this comparison.

This work contributes to the understanding of physical mechanisms that control flashback, or more appropriately combustion recession, in diesel sprays. A large dataset, comprising many fuels, injection pressures, ambient temperatures, ambient oxygen concentrations, ambient densities, and nozzle diameters is used to explore experimental trends for the behavior of combustion recession. Then, a reduced-order model, capable of modeling non-reacting and reacting conditions, is used to help interpret the experimental trends. Finally, the reduced-order model is used to predict how a controlled ramp-down rate-of-injection can enhance the likelihood of combustion recession for conditions that would not normally exhibit combustion recession. In general, fuel, ambient conditions, and the end-of-injection transient determine the success or failure of combustion recession.

Using measurable physical input variables, an implementable control algorithm for parallel architecture plug-in and non-plug-in hybrid electric vehicle (PHEV and HEV) powertrains is presented. The control of the electric drive is based on an algebraic mapping of the accelerator pedal position, the battery state-of-charge (SOC), and the vehicle velocity into a motor controller input torque command. This mapping is developed using a sequential linearization control (SLC) methodology. The internal combustion engine (ICE) control uses a modified accelerator pedal to throttle plate angle using an adjustable gain parameter that, in turn, determines the sustained battery SOC. Searches over an admissible control space or the use of pre-defined look-up tables are thus avoided. Actual on-road results for a Ford Explorer with a through-the-road (TTR) hybrid powertrain using this control methodology are presented.

A plug-in hybrid electric vehicle (PHEV) design with design parameters electric motor size, engine size, battery capacity, and battery chemistry type, is optimized with minimum cost as a measure of merit. The PHEV is required to meet a fixed set of performance constraints consisting of 0-60 mph acceleration, 50-70 mph acceleration, 0-30 mph acceleration in all electric operation, top speed, grade ability, and all electric range. The optimization is carried out for values of all electric range of 10, 20, and 40 miles. The social and economic impacts of the optimum designs in terms of reduced gasoline consumption and carbon emissions reduction are calculated. Argonne National Laboratory's Powertrain Systems Analysis Toolkit is used to simulate the performance and fuel economy of the PHEV designs. The costs of different PHEV components and the present value of battery replacements over the vehicle's life are used to determine the design's drivetrain cost.

Compressive load capacity of composite lattice structures are studied. The objective of this research is to investigate the buckling strength of composite lattice structures and to design the most weight efficient structure with the highest buckling load. Buckling strength of both the composite lattice cylindrical and conical shells under axial compressive loads are examined. The main emphasis is placed on the effects of geometric constraints and the optimal design of the structures. In this research, various constraints are studied and the optimal structure which gives the highest strength to weight ratio is obtained. Moreover, these structures can be constructed by filament winding, the manufacturing process can be automated, and the costs can be greatly reduced.

As an element of a design optimization study of high speed civil transport (HSCT), response surface equations (RSEs) were developed with the goal of accurately predicting the sideline, takeoff, and approach noise levels for any combination of selected design variables. These RSEs were needed during vehicle synthesis to constrain the aircraft design to meet FAR 36, Stage 3 noise levels. Development of the RSEs was useful as an application of response surface methodology to a previously untested discipline. Noise levels were predicted using the Aircraft Noise Prediction Program (ANOPP), with additional corrections to account for inlet and exhaust duct lining, mixer-ejector nozzles, multiple fan stages, and wing reflection. The fan, jet, and airframe contributions were considered in the aircraft source noise prediction.

This paper outlines the design of a part transport and loading/unloading automation system for a cylindrical die thread roller, enumerating many of the design decisions encountered. Specifically, a transport tray system is proposed and prototyped as a benchmark for factory automation. Details of an automation system which will interface with the proposed transport tray system are discussed. A gripping system which accommodates a wide variety of fastener head styles is developed to work in conjunction with the tray concept, and prototyped with favorable results.

End-of-injection transients have recently been shown to be important for combustion and emissions outcomes in diesel engines. The objective of this work is to develop an understanding of the coupling between end-of-injection transients and the propensity for second-stage ignition in mixtures upstream of the lifted diesel flame, or combustion recession. An injection system capable of varying the end-of-injection transient was developed to study single fuel sprays in a newly commissioned optically-accessible spray chamber under a range of ambient conditions. Simultaneous high-speed optical diagnostics, namely schlieren, OH* chemiluminescence, and broadband luminosity, were used to characterize the spatial and temporal development of combustion recession after the end of injection.

Test methods and data acquisition system specifications are described for measurements of the energy consumption of the control system of a servo-pump continuously variable transmission (CVT). Dynamic measurements of the power consumption of the servo-pump CVT control system show that the control system draws approximately 18.9 W-hrs of electrical energy over the HWFET cycle and 13.6 W-hrs over the 505 cycle. Sample results are presented of the dynamic power consumption of the servo-pump system under drive cycle conditions. Steady state measurements of the control power draw of the servo-pump CVT show a peak power consumption of 271 W, including lubrication power. The drive-cycle averaged and steady state energy consumption of the servo-pump CVT are compared to conventional CVT pump technologies.

This paper describes a machine to quarry construction material, sinter walls, and assemble future space station modules. In prior work, we explored the solar energy requirements to build a 50m diameter, 50m high, cylindrical module out of pulverized rock from a Near-Earth Object, using tailored radio wave fields. In this paper, we describe the issues in the conceptual design of the robotic construction machines. The 4-legged Rock breaker is designed to fit the payload bay of a modern heavy-lift booster to reach Low Earth Orbit, and primary solar-sail propulsion for most of its journey. It uses beamed microwave energy for its cutting operations. Rotating, telescoping arms use integrated laser/plasma jet cutter arrays to dig trenches in spiral patterns which will form blocks of material. Cut blocks are sent into a toroidal cloud of material for use in the force field tailoring for automatic module formation.

In order to improve understanding of the primary atomization process for diesel-like sprays, a collaborative experimental and computational study was focused on the near-nozzle spray structure for the Engine Combustion Network (ECN) Spray D single-hole injector. These results were presented at the 5th Workshop of the ECN in Detroit, Michigan. Application of x-ray diagnostics to the Spray D standard cold condition enabled quantification of distributions of mass, phase interfacial area, and droplet size in the near-nozzle region from 0.1 to 14 mm from the nozzle exit. Using these data, several modeling frameworks, from Lagrangian-Eulerian to Eulerian-Eulerian and from Reynolds-Averaged Navier-Stokes (RANS) to Direct Numerical Simulation (DNS), were assessed in their ability to capture and explain experimentally observed spray details. Due to its computational efficiency, the Lagrangian-Eulerian approach was able to provide spray predictions across a broad range of conditions.

The atomization and initial spray formation processes in direct injection engines are not well understood due to the experimental and computational challenges associated with resolving these processes. Although different physical mechanisms, such as aerodynamic-induced instabilities and nozzle-generated turbulence and cavitation, have been proposed in the literature to describe these processes, direct validation of the theoretical basis of these models under engine-relevant conditions has not been possible to date. Recent developments in droplet sizing measurement techniques offer a new opportunity to evaluate droplet size distributions formed in the central and peripheral regions of the spray. There is therefore a need to understand how these measurements might be utilized to validate unobservable physics in the near nozzle-region.