Search Results

The objective of this paper is to illustrate the methods and tools developed to size and synthesize a stopped rotor/wing vehicle using a reaction drive system, including how this design capability is incorporated into a sizing and synthesis tool, VASCOMP II. This new capability is used to design a vehicle capable of performing a V-22 escort mission, and a sized vehicle description with performance characteristics is presented. The resulting vehicle is then compared side-by-side to a variable diameter tiltrotor designed for the same mission. Results of this analysis indicate that the reaction-driven rotor concept holds promise relative to alternative concepts, but that the variable diameter tiltrotor has several inherent performance advantages. Additionally, the stopped rotor/wing needs considerably more development to reach maturity.

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.

Motor vehicle crashes involving child Vulnerable Road Users (VRUs) remain a critical public health concern in the United States. While previous studies successfully utilized the crash scenario typology to examine traffic crashes, these studies focus on all types of motor vehicle crashes thus the method might not apply to VRU crashes. Therefore, to better understand the context and causes of child VRU crashes on the U.S. road, this paper proposes a multi-step framework to define crash scenario typology based on the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS). A comprehensive examination of the data elements in FARS and CRSS was first conducted to determine elements that could facilitate crash scenario identification from a systematic perspective. A follow-up context description depicts the typical behavioral, environmental, and vehicular conditions associated with an identified crash scenario.

Developing a new technology requires decision-makers to understand the technology's implications on an organization's objectives, which depend on user needs targeted by the technology. If these needs are common between two organizations, collaboration could result in more efficient technology development. For hybrid truck design, both commercial manufacturers and the military have similar performance needs. As the new technology penetrates the truck market, the commercial enterprise must quantify how the hybrid's superior fuel efficiency will impact consumer purchasing and, thus, future enterprise profits. The Army is also interested in hybrid technology as it continues its transformation to a more fuel-efficient force. Despite having different objectives, maximizing profit and battlefield performance, respectively, the commercial enterprise and Army can take advantage of their mutual needs.

The fidelity of the hybrid electric vehicle simulation is increased with the integration of a computationally-efficient finite-element based electric machine model, in order to address optimization of component design for system level goals. In-wheel electric motors are considered because of the off-road military application which differs significantly from commercial HEV applications. Optimization framework is setup by coupling the vehicle simulation to the constrained optimization solver. Utilizing the increased design flexibility afforded by the model, the solver is able to reshape the electric machine's efficiency map to better match the vehicle operation points. As the result, the favorable design of the e-machine is selected to improve vehicle fuel economy and reduce cost, while satisfying performance constraints.

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.

The quantification of aircraft survivability in modern battlefield environments is a complex mathematical problem. In general, consideration must be given to the quantification of aircraft vulnerability to individual weapon systems, single encounter aircraft survivability, and the mathematical mapping of single encounter aircraft survivability into mission attrition. A methodology for quantifying the impacts of electronic warfare (EW) upon aircraft survivability is realized by the General Effectiveness Methodology (GEM) which is based upon a hierarchy of computer models. This paper describes this hierarchy of computer simulation tools which extensively employs probability theory to estimate the various engagement events such as aircraft detection, acquisition, missile launch, missile intercept, and probability of aircraft kill.

The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

Vehicle structure crashworthiness design is one of the most challenging problems in product development and it has been studied for decades. Challenges still remain, which include developing a reliable and systematic approach for general crashworthiness design problems, which can be used to design an optimum vehicle structure in terms of topology, shape, and size, and for both structural layout and material layout. In this paper, an advanced and systematic approach is presented, which is called Magic Cube (MQ) approach for crashworthiness design. The proposed MQ approach consists of three major dimensions: Decomposition, Design Methodology, and General Considerations. The Decomposition dimension is related to the major approaches developed for the crashworthiness design problem, which has three layers: Time (Process) Decomposition, Space Decomposition, and Scale Decomposition.

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.

The reach capability of drivers is currently represented in vehicle design practice in two ways. The SAE Recommended Practice J287 presents maximum reach capability surfaces for selected percentiles of a generic driving population. Driver reach is also simulated using digital human figure models. In typical applications, a family of figure models that span a large range of the target driver population with respect to body dimensions is positioned within a digital mockup of the driver's workstation. The articulated segments of the figure model are exercised to simulate reaching motions and driver capabilities are calculated from the constraints of the kinematic model. Both of these current methods for representing driver reach are substantially limited. The J287 surfaces are not configurable for population characteristics, do not provide the user with the ability to adjust accommodation percentiles, and do not provide any guidance on the difficulty of reaches that are attainable.

The paper describes a new hybrid vehicle design option having very low energy storage capability, and in particular, a parallel hybrid with hydraulic storage and reapplication of braking energy. The operating efficiency of the propulsion system at light loads is substantially improved by splitting the engine into two segments, and finding ways of shutting down one or both engine segments whenever possible. The hybrid vehicle utilizes primarily current technologies. A diesel powered parallel hybrid as described demonstrates a reduction in fuel consumption of 53.9% on a volume basis when compared with an equivalent baseline vehicle.

System effectiveness has become the prime metric for the evaluation of military aircraft. As such, it is the designer's goal to maximize system effectiveness. Industry documents indicate that all future military aircraft will incorporate signature reduction as an attempt to improve system effectiveness. Today's operating environments demand low observable aircraft which are able to reliably eliminate valuable, time critical targets. Thus, it is desirable to be able to evaluate the signatures of a vehicle, as well as the influence of signatures on the systems effectiveness of a vehicle. Previous studies have shown that shaping of the vehicle is one of the most important contributors to radar cross section and must be considered from the very beginning of the design process. This research strives to meet these needs by developing a parametric geometry radar cross section prediction tool.

Several approaches to robust design have been proposed in the past. Only few acknowledged the paradigm shift from performance based design to design for cost. The incorporation of economics in the design process, however, makes a probabilistic approach to design necessary, due to the inherent ambiguity of assumptions and requirements as well as the operating environment of future aircraft. The approach previously proposed by the authors, linking Response Surface Methodology with Monte Carlo Simulations, has revealed itself to be cumbersome and at times impractical for multi-constraint, multi-objective problems. In addition, prediction accuracy problems were observed for certain scenarios that could not easily be resolved. Hence, this paper proposes an alternate approach to probabilistic design, which is based on a Fast Probability Integration technique.

The objective of this paper is to examine ways in which to implement probabilistic design methods in the aircraft engine preliminary design process. Specifically, the focus is on analytically determining the impact of uncertainty in engine component performance on the overall performance of a notional large commercial transport, particularly the impact on design range, fuel burn, and engine weight. The emphasis is twofold: first is to find ways to reduce the impact of this uncertainty through appropriate engine cycle selections, and second is on finding ways to leverage existing design margin to squeeze more performance out of current technology. One of the fundamental results shown herein is that uncertainty in component performance has a significant impact on the overall aircraft performance (it is on the same order of magnitude as the impact of the cycle itself).

In early phases of conceptual design stages for developing a new car in the modern automobile industry, the lack of systematic methodology to efficiently converge to an agreement between the aesthetics and aerodynamic performance tremendously increases budget and time. During these procedures, one of the most important tasks is to create geometric information which is versatilely morphable upon the demands of both of stylists and engineers. In this perspective, this paper proposes a Spline-based Modeling Algorithm (SMA) to implement into performing aerodynamic design optimization research based on CFD analysis. Once a 3-perspective schematic of a car is given, SMA regresses the backbone boundary lines by using optimum polynomial interpolation methods with the best goodness of fit, eventually reconstructing the 3D shape by linearly interpolating from the extracted boundaries minimizing loss of important geometric features.

Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.

One the most critical barriers to the advancement of Personal Air Vehicles in today's market environment is that the technological capabilities can never seem to outweigh the risks associated with financing such an endeavor. To address such a need, a system dynamics approach with the capability to model the uncertainties in the supply chain is presented in this paper. The overall modeling framework is first presented and the modeling process of the various relevant elements, such as demand prediction and manufacturer analysis, is then described. The aim of this research is ultimately to assess the viability of a next-generation aircraft program beyond the static confines of a net present value approach, through the inclusion of dynamic events and uncertainties that can occur throughout the life-cycle of the aircraft.

A technique is proposed for examining complex behaviors in the “pilot - vehicle - operational conditions” system using an autonomous situational model of flight. The goal is to identify potentially critical flight situations in the system behavior early in the design process. An exhaustive set of flight scenarios can be constructed and modeled on a computer by the designer in accordance with test certification requirements or other inputs. Distinguishing features of the technique include the autonomy of experimentation (the pilot and a flight simulator are not involved) and easy planning and quick modeling of complex multi-factor flight cases. An example of mapping airworthiness requirements into formal scenarios is presented. Simulation results for various flight situations and aircraft types are also demonstrated.

Multiple models to estimate motion sickness (MS) have been proposed in the literature; however, few capture the influence of visual cues, limiting the models’ ability to predict MS that closely matches experimental MS data. This is especially significant in the presence of conflicts between visual and vestibular sensory signals. This paper provides an analysis of the gaps within existing MS estimation models and addresses these gaps by proposing the visual-vestibular motion sickness (VVMS) model. In this paper, the structure of the VVMS model, associated model parameters, and mathematical and physiological justification for selecting these parameters are presented. The VVMS model integrates vestibular sensory dynamics, visual motion perception, and visual-vestibular cue conflict to determine the conflict between the sensed and true vertical orientation of the passenger.