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Turboelectric propulsion is a technology that can potentially reduce aircraft noise, increase fuel efficiency, and decrease harmful emissions. In a turbo-electric system, the propulsor (fans) is no longer connected to the turbine through a mechanical connection. Instead, a superconducting generator connected to a gas turbine produces electrical power which is delivered to distributed fans. This configuration can potentially decrease fuel burn by 10% [1]. One of the primary challenges in implementing turboelectric electric propulsion is designing the power distribution system to transmit power from the generator to the fans. The power distribution system is required to transmit 40 MW of power from the generator to the electrical loads on the aircraft. A conventional aircraft distribution cannot efficiently or reliably transmit this large amount of power; therefore, new power distribution technologies must be considered.

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.

The success of a modern, complex engineering program is inherently a dynamic economic exercise. Because of this it is not possible to fully grasp what decisions are important to the success of a program using only the typical static or “frozen” design methods and processes. This paper attempts to provide a basic understanding of these design processes and illustrate what they leave to be desired when used in a true market environment. Further, this paper illustrates a dynamic method using tools from engineering, management, and finance to overcome these weaknesses. The dynamic environment allows decision parameters and metrics to change, along with the potential for true competition. Furthermore, it allows the engineer to determine which design choices matter most to the creation of a successful program and how to make the most appropriate choices in the face of uncertainty.

This paper presents a quantitative process to track the progress of technology developments within NASA’s Vehicle Systems Program (VSP) as implemented on a Supersonic Business Jet (SBJ). The process, called the Technology Metric Assessment and Tracking (TMAT) process, accounts for the temporal aspects of technology development programs such that technology portfolio assessments, in the form of technological progress towards VSP sector goals, may be tracked and assessed. Progress tracking of internal research and development programs is an essential element to successful strategic endeavors and justification of the pursuit of capital projects [1].

Although market research has indicated that there is significant demand for a supersonic business aircraft, development of a feasible concept has proven difficult. Two factors contributing to this difficulty are the uncertain nature of the vehicle’s requirements and the fact that conventional design methods are inadequate to solve such non-traditional problems. This paper describes the application of a multiobjective genetic algorithm to the design space exploration of such a supersonic business jet. Results obtained using this method are presented, and give insight into the important decisions that must be made at the early stages of a design project.

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.

This paper discusses the use of a Multi-Objective Genetic Algorithm to optimize a technology portfolio for a commercial transport. When incorporating technologies into a conceptual design, there are often multiple competing objectives that determine the benefits and costs of a certain portfolio. The set of designs that achieves the best values of these objectives will fall along a Pareto front that outlines the tradeoffs which will give the optimal design. Multi-Objective Genetic Algorithms determine the Pareto set by giving higher priority to dominant portfolios in the evolutionary optimization techniques of selection and reproduction. When determining the final Pareto optimal set it is important to ensure that only compatible portfolios of technologies are present.

The projection of aeroelastic constraints in the design space has long been a want in the design process of vehicles. These properties are usually not established accurately until later phases of design. The desire is to bring another interactive constraint to the conceptual design phase and allow the designer to see the impact of design decisions on aeroelastic characteristics. Even though a number of analysis and optimization tools have been developed to support aeroelastic analysis and optimization in the flight vehicle design process, the toolbox is far from being complete. The results often cannot be obtained in a manner timely enough and the natural division of the engineering team into specialty groups is not supported very well by the aerodynamic-structures monolithic codes typically in the above toolbox. The monolithic codes are also not amenable to the use of concurrent processing now made available by computer technology.

Commercial and independent market assessments continue to reveal a strong market desire for a supersonic business jet capable of meeting the requirements for supersonic, overland flight. However, the challenge of meeting the as-yet undefined regulations for overland flight, as well as meeting current and future noise and emission regulations, is daunting. An integrated modeling and simulation environment, based on the creation of response surface metamodels, allows for the rapid evaluation of a design space. From this environment the effects on metrics such as emissions, economics, sonic boom profiles and noise levels can rapidly be seen and manipulated. Such an environment also allows the application of technologies to the vehicle in order to evaluate their potential impact on the system-level metrics.

In today's business climate, aerospace companies are more than ever in need of rational methods and techniques that provide insights as to the best strategies which may be pursued for increased profitability and risk mitigation. However, the use of subjective, anecdotal decision-making remains prevalent due to the absence of analytical methods capable of capturing and forecasting future needs. Negotiations between airframe and engine manufacturers could benefit greatly from a structured environment that facilitates efficient, rational, decision-making. Creation of such an environment can be developed through a parametric physics-based, stochastic formulation that uses Response Surface Equations as meta-models to expedite the process.

In this paper, a brief overview is given of the different alternatives to an integrating computational framework. A new framework will be introduced, which incorporates the latest computational techniques and more importantly a mind-set emphasizing flexibility, modularity, portability and re-usability. This introduction will include a thorough review of the fundamental design decisions that went into developing this new integrated computational framework. Distributed object computing extends an object-oriented system which allows objects to interact across heterogenous networks and interoperate as a unified whole. Integrated computing frameworks are discussed, together with data transport techniques such as Extensible Markup Language (XML) and Simple Object Access Protocol (SOAP) to achieve platform, code and meta-model independent integration.

Current robust design methods rely heavily on meta-modeling techniques to reduce the total computational effort of probabilistic explorations to a combinatorially manageable size. Historically most of these meta-models were in the form of Response Surface Equations (RSE). Recently there has been interest in supplementing the RSE with techniques that better handle non-linear phenomena. One technique that has been identified is the Gaussian Process (GP). The GP has fewer initial assumptions when compared to the linear methods used by RSEs and, therefore, fewer limitations. The initial implementation and employment techniques proposed in current literature for use with the GP are barely modified versions of those used for RSEs. A better, more tailored technique needs to be developed to properly make use of the nature of the GP, and minimize the effect of some of its limitations. Such a technique would allow for rapid development of a reusable, computationally efficient and accurate GP.

A solid business case is highly dependent upon a strategic technology research and development plan in the early phases of product design. The embodiment of a strategic technology development plan is the identification and subsequent funding of high payoff technology programs that can maximize a company’s return on investment, which entails both performance and economic objectives. This paper describes a technique whereby the high payoff technologies may be identified across multiple platforms to quantitatively justify resource allocation decisions and investment opportunities. A proof of concept investigation was performed on a fleet of subsonic, commercial aircraft.

A method to identify the topology of an aerospace system’s requirements space, specifically the location and type of the discontinuities that occur at the boundaries of the available technology and the physics of the system, allows the designer to make decisions as to the desirability of a specific solution state. Additionally, since a given set of requirements may produce multiple solutions the designer can compare his/her solution to other potential solutions. This allows an assessment of the requirements risk associated with a specific design. This paper addresses the need to visualize and understand the topology of the requirements space for a Rapid Response Strike System.

Several unique aspects of the design of hypersonic aerospace systems necessitate a truly multidisciplinary approach from the outset of the program. These coupled with a vague or changing requirements environment, provide an impetus for the development of a systematic and unified approach for the exploration and evaluation of alternative hypersonic vehicle concepts. The method formulated and outlined in this paper is founded upon non-deterministic conceptual & preliminary design formulations introduced over the past decade and introduces the concept of viewing system level requirements in a similar manner. The proposed method is then implemented for the concept exploration and design of a Hypersonic Strike Fighter in the presence of ambiguous open and/or evolving requirements.

The desire to facilitate the conceptual and preliminary design of hypersonic cruise vehicles has created the need for simple, fast, versatile, and trusted aerodynamic analysis tools. Metamodels representing physics-based engineering codes provide instantaneous access to calibrated tools. Nonlinear transformations extend the capability of metamodels to accurately represent a large design space. Independence, superposition, and scaling properties of the hypersonic engineering method afford an expansive design space without traditional compounding penalties. This one-time investment results in aerodynamic and volumetric metamodels of superior quality and versatility which may be used in many forms throughout early design. As a module, they can be an integral component within a multidisciplinary analysis and optimization package. Aerodynamic polars they produce may provide performance information for mission analysis.

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.

The accepted paradigm in aerospace systems design was to design systems sequentially and iteratively to maximize performance based on minimum weight. The traditional paradigm does not work in the rapidly changing global environment. A paradigm shift from the norm of “design for performance” to “design for affordability and quality” has been occurring in recent decades to respond to the changing global environment. Observations were made regarding new tenets needed to bridge the gap from the old to the new. These tenets include new methods and techniques for designing complex systems due to uncertainty and mulit-dimensionality, consideration of the life cycle of the system, and the methods needed to assess breakthrough technologies to meet aggressive goals of the future. The Technology Identification, Evaluation, and Selection method was proposed as a possible solution to the paradigm shift.

In current design practices, safety, operational and handling criteria are often overlooked until late design stages due to the difficulty in capturing such criteria early enough in the design cycle and in the presence of limited and uncertain knowledge. Virtual (flight) testing and evaluation, based on autonomous modeling and simulation, is proposed as a solution to this shortcoming. The methodology enables one to evaluate vehicle behavior in relatively complex situations through a series of specific flight scenarios. Bringing this methodology to conceptual design requires the creation of an automatic link between the design database and the autonomous flight simulation environment. This paper describes the creation of such a link and an implementation of the Virtual Testing and Evaluation methodology with the use of an advanced design concept.

An evolved version of the Technology Identification, Evaluation, and Selection (TIES) method is presented that provides techniques for quantifying technological uncertainty associated with immature technologies. Uncertainty in this context implies forecasting. Forecasting the impact of immature technologies on a system is needed to provide increased knowledge to a decision-maker in the conceptual and preliminary phases of aircraft design. The increased knowledge allows for proper allocation of company resources and program management. The TIES method addresses the milestones encountered during a technology development program, the sources of uncertainty during that development, a potential method for bounding and forecasting the uncertainty, and a means to quantify the impact of any emerging technology. A proof of concept application was performed on a High Speed Civil Transport concept due to its technically challenging customer requirements.