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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 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].

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.