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The objective of this paper is to develop a generalized loss management model to account for the usage of thermodynamic work potential in vehicles of any type. The key to accomplishing this is creation of a differential representation for vehicle loss as a function of operating condition. This differential model is then integrated through time to obtain an analytical estimate for total usage (and loss) of work potential consumed by each loss mechanism present during vehicle operation. The end result of this analysis is a better understanding of how the work potential initially present in the fuel, batteries, etc. is partitioned amongst all losses relevant to the vehicle's operation. The loss partitioning estimated from this loss management model can be used in conjunction with cost accounting systems to gain a better understanding of underlying drivers on vehicle manufacturing and operating costs.

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.

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.

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.

Although the design phase can account for a sizable amount of the resources consumed during the product realization process, the time and costs associated with the design process are often neglected when making design decisions. To investigate this issue, we define a process-centric decision model in which the design-phase consumption of resources, such as time and money, is explicitly modeled. While it is clear that the utility of a design is almost always directly impacted by the monetary costs of the design process, our decision model also accounts for the fact that the profit earned by a product depends strongly on its launch date. The decision model allows us thus to consider the trade-off between the time necessary for analysis and the improvement in product quality that results from the analysis. The decision model is sufficiently generic that almost any set of beliefs about the alternatives or analyses, as well as any utility-based preference structure can be modeled.

General Motors has introduced a Two-Mode Transmission (2-MT) that provides significant improvements over the Toyota THS-II transmission. These improvements are achieved by employing additional planetaries with clutches and brakes to switch from a Mode-1 to Mode-2 as vehicle speed increases. In addition the 2-MT has four fixed-gear ratios that provide for a purely mechanical energy path from the IC engine to the driven wheels with the electric machines also able to provide additional driving torque. The purpose of this present paper is to extend the methodology in a previous paper [1] to include the 2-MT, thereby presenting an analytic foundation for its operation. The main contribution in this analysis is in the definition of dimensionless separation factors, defined in each mode that govern the power split between the parallel mechanical and electrical energy paths from the IC engine to the driven wheels.

In today’s atmosphere of lower U.S. defense spending and reduced research budgets, determining how to allocate resources for research and design has become a critical and challenging task. In the area of aircraft design there are many promising technologies to be explored, yet limited funds with which to explore them. In addition, issues concerning uncertainty in technology readiness as well as the quantification of the impact of a technology (or combinations of technologies), are of key importance during the design process. The methodology presented in this paper details a comprehensive and structured process in which to explore the effects of technology for a given baseline aircraft. This process, called Technology Impact Forecasting (TIF), involves the creation of a forecasting environment for use in conjunction with defined technology scenarios. The advantages and limitations of the method will be discussed, as well its place in an overall methodology used for technology infusion.

An affordable technique is proposed for fast quantitative analysis of aerobatics and other complex flight domains of highly maneuverable aircraft. A generalized autonomous situational model of the “pilot (automaton) – vehicle – operational environment” system is employed as a “virtual test article”. Using this technique, a systematic knowledge of the system behavior in aerobatic flight can be generated on a computer, much faster than real time. This information can be analyzed via a set of knowledge mapping formats using a 3-D graphics visualization tool. Piloting and programming skills are not required in this process. Possible applications include: aircraft design and education, applied aerodynamics, flight control systems design, planning and rehearsal of flight test and display programs, investigation of aerobatics-related flight accidents and incidents, physics-based pilot training, research into new maneuvers, autonomous flight, and onboard AI.

Battery modeling is of major concern for Hybrid Electric Vehicle (HEV) and Electric vehicle (EV) modeling. The major issue lies in characterizing the battery power output in relation to battery's State of Charge (SOC) in various application conditions. In particular, the challenge is associated with the difficulty that the characteristic parameters of the battery, i.e. the accurate data on the open circuit voltage and the internal resistance are hardly obtainable in practical conditions. In this paper, a battery capacity representation and a practical way of battery modeling is introduced for simulation model development based on the experimental data. A realistic way of battery SOC representation is generated from the battery output data. Empirical formulation is derived from the data to correlate the battery current, voltage output with the battery SOC.

Tools are now publicly available that can potentially help a company assess the impact of its water use and risks in relation to their global operations and supply chains. In this paper we describe a comparative analysis of two publicly available tools, specifically the WWF/DEG Water Risk Filter and the WBCSD Global Water Tool that are used to measure the water impact and risk indicators for industrial facilities. By analyzing the risk assessments calculated by these tools for different scenarios that include varying facilities from different industries, one can better gauge the similarities and differences between these water strategy tools. Several scenarios were evaluated using the water tools, and the results are compared and contrasted. As will be shown, the results can vary significantly.

A design process is formulated and implemented for the taxonomy selection and system-level optimization of an Efficient Multi-Mach Aircraft Current Technology Concept and an Advanced Concept. Concept space exploration of taxonomy alternatives is performed with multi-objective genetic algorithms and a Powell’s method scheme for vehicle optimization in a multidisciplinary modeling and simulation environment. A dynamic sensitivity visualization analysis tool is generated for the Advanced Concept with response surface equations.

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.

Over the past few years, modern aircraft design has experienced a paradigm shift from designing for performance to designing for affordability. This paper contains a probabilistic approach that will allow traditional deterministic design methods to be extended to account for disciplinary, economic, and technological uncertainty. The probabilistic approach was facilitated by the Fast Probability Integration (FPI) technique; a technique which allows the designer to gather valuable information about the vehicle's behavior in the design space. This technique is efficient for assessing multi-attribute, multi-constraint problems in a more realistic fashion. For implementation purposes, this technique is applied to illustrate how both economic and technological uncertainty associated with a Very Large Transport aircraft may be assessed.

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.

A multidisciplinary design study considering the impact of Active Aeroelastic Wing (AAW) technology on the structural wing weight of a lightweight fighter concept is presented. The study incorporates multidisciplinary design optimization (MDO) and response surface methods to characterize wing weight as a function of wing geometry. The study involves the sizing of the wing box skins of several fighter configurations to minimum weight subject to static aeroelastic requirements. In addition, the MDO problem makes use of a new capability, trim optimization for redundant control surfaces, to accurately model AAW technology. The response surface methodology incorporates design of experiments, least squares regression, and makes use of the parametric definition of a structural finite element model and aerodynamic model to build response surface equations of wing weight as a function of wing geometric parameters for both AAW technology and conventional control technology.

Several research institutions and universities have taken on the challenge of providing solutions for accessible and universally designed workplace accommodations with a focus on people with disabilities. Accessible Design is a subset of what is termed Universal Design. Where Universal Design covers the design of products, systems and environments for all people and encompasses all design principles, Accessible Design focuses on principles that extend the standard design process to those people with some type of performance limitation. In order for individuals with disabiltities to gain better access to the work environments and the products that facilitate independence, health, safety, and social participation a multi-disciplined approach to the research is needed to identify needs and challenges of the targeted population.

The enabling of advanced design methods in an internet-capable framework will be discussed in this paper. The resulting framework represents the next generation of design and analysis capability in which engineering decision- making can be done by geographically distributed team members. A new internet technology called the lean-server approach is introduced as a mechanism for granting Web browser access to frameworks and domain analyses. This approach has the underpinnings required to support these next generation frameworks - collaboratories. A historical perspective of design frameworks is discussed to provide an understanding of the design functionality that is expected from framework implementations to insure design technology advancement. Two research areas were identified as being important to the development of collaboratories: design portals and collaborative methods.