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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.

The Conceptual Aerospace Systems Design and Analysis Toolkit (CASDAT) provides a baseline assessment capability for the Air Force Research Laboratory. The historical development of CASDAT is of benefit to the design research community because considerable effort was expended in the classification of the analysis tools. Its implementation proves to also be of importance because of the definition of assessment use cases. As a result, CASDAT is compatible with accepted analysis tools and can be used with state-of-the-art assessment methods, including technology forecasting and probabilistic design.

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.

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.

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.

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.

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.

A family of Very Large Transport (VLT) concepts were studied as an implementation of the affordability aspects of the Robust Design Simulation (RDS) methodology which is based on the Integrated Product and Process Development (IPPD) initiative that is sweeping through industry. The VLT is envisioned to be a high capacity (600 to 1000 passengers), long range (∼7500 nm), subsonic transport. Various configurations with different levels of technology were compared, based on affordability issues, to a Boeing 747-400 which is a current high capacity, long range transport. The varying technology levels prompted a need for an integration of a sizing/synthesis (FLOPS) code with an economics package (ALCCA). The integration enables a direct evaluation of the added technology on a configuration economic viability.

This paper critically evaluates the use of Neural Networks (NNs) as metamodels for design applications. The specifics of implementing a NN approach are researched and discussed, including the type and architecture appropriate for design-related tasks, the processes of collecting training and validation data, and training the network, resulting in a sound process, which is described. This approach is then contrasted to the Response Surface Methodology (RSM). As illustrative problems, two equations to be approximated and a real-world problem from a Stability and Controls scenario, where it is desirable to predict the static longitudinal stability for a High Speed Civil Transport (HSCT) at takeoff, are presented. This research examines Response Surface Equations (RSEs) as Taylor series approximations, and explains their high performance as a proven approach to approximate functions that are known to be quadratic or near quadratic in nature.

Traditional historical-data based design processes are clearly inappropriate for morphing vehicles. There are no historical data for these type of configurations, the appropriate mission for this class of vehicles is unknown, and there are many unique aspects of a morphing vehicle that are dependent on the specific concept chosen. The design process proposed in this paper attempts to account for these difficulties in a flexible and transparent manner while leveraging existing tools and processes wherever possible.

The ultimate goal of knowledge-based aircraft design, pilot training and flight operations is to make flight safety an inherent, built-in feature of the flight vehicle, such as its aerodynamics, strength, economics and comfort are. Individual flight accidents and incidents may vary in terms of quantitative characteristics, circumstances, and other external details. However, their cause-and-effect patterns often reveal invariant structure or essential causal chains which may re-occur in the future for the same or other vehicle types. The identification of invariant logical patterns from flight accident reports, time-histories and other data sources is very important for enhancing flight safety at the level of the ‘pilot - vehicle -operational conditions’ system. The objective of this research project was to develop and assess a method for ‘mining’ knowledge of typical cause-and-effect patterns from flight accidents and incidents.

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.

A Hypersonic Strike Fighter (HSF) would provide many benefits over current fighters, including increased effectiveness and survivability. However, there are many design challenges to developing such a vehicle. Therefore the conceptual design of an HSF requires the development of new tools and methods to analyze and select vehicle concepts. A parametric method was developed to determine aerodynamic characteristics of hypersonic vehicles in a rapid, automated way. This parametric method and other tools were then used to select a baseline design and optimize this baseline for the notional mission.

Market forecasts predict a potentially large market for a Quiet Supersonic Business Jet provided that several technical hurdles are overcome prior to fielding such a vehicle. In order to be economically viable, the QSJ must be able to fly at supersonic speeds overland and operate from regional airports in addition to meeting government noise and emission requirements. As a result of these conflicting constraints on the design, the process of selecting a configuration for low sonic boom is a difficult one. Response Surface Methodology along with physics-based analysis tools were used to create an environment in which the sonic boom can be studied as a function of design and mission parameters. Ten disciplinary codes were linked with a sizing and synthesis code by using a commercial wrapper in order to calculate the required responses with the desired level of fidelity.

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.

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.

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.

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.

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.