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A key issue in complex systems design is measuring the ‘goodness’ of a design, i.e. finding a criterion through which a particular design is determined to be the ‘best’. Traditional choices in aerospace systems design, such as performance, cost, revenue, reliability, and safety, individually fail to fully capture the life cycle characteristics of the system. Furthermore, current multi-criteria optimization approaches, addressing this problem, rely on deterministic, thus, complete and known information about the system and the environment it is exposed to. In many cases, this information is not be available at the conceptual or preliminary design phases. Hence, critical decisions made in these phases have to draw from only incomplete or uncertain knowledge. One modeling option is to treat this incomplete information probabilistically, accounting for the fact that certain values may be prominent, while the actual value during operation is unknown.

This paper outlines a comprehensive, structured, and robust methodology for decision making in the early phases ofaircraft design. The proposed approach is referred to as the Technology Identification, Evaluation, and Selection (TIES) method. The seven-step process provides the decision maker/designer with an ability to easily assess and trade-off the impact of various technologies in the absence of sophisticated, time-consuming mathematical formulations. The method also provides a framework where technically feasible alternatives can be identified with accuracy and speed. This goal is achieved through the use of various probabilistic methods, such as Response Surface Methodology and Monte Carlo Simulations. Furthermore, structured and systematic techniques are utilized to identify possible concepts and evaluation criteria by which comparisons could be made.

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.

Societal demands of recent years have increasingly pressured the development of greener technologies in all sectors of the nation's transportation infrastructure, including that of civilian aviation. This study explores the concept of electric-drive aeropropulsion, aided by high-temperature superconducting technology, as an enabler for enhancing the environmental characteristics at the air-vehicle level. Potential improvements in the areas of aircraft noise, emissions, and energy efficiency are discussed in the context of supporting the latest strategic goals of leading governmental organizations.

Unfortunately, the promises of efficient, clean, quiet power that fuel cells offer are balanced by extremely low power densities and great infrastructure-related challenges. Studies by government and industry have investigated their feasibility for primary propulsion in light aircraft. These studies have produced mixed results but have tended to rely on integrating fuel cells into existing airframes, with respectably-performing light sport planes being turned into underpowered show planes with horribly compromised range and payload capabilities. Fuel cells today are in the earliest phases of technological development. As an aircraft propulsion system, they are as advanced as the Wright's reciprocating engine was a hundred years ago.

The High Speed Civil Transport (HSCT), a supersonic commercial transport currently under development, presents several challenges to traditional conceptual design. The current historical database used by many commercial transport design processes only include data for subsonic transports and therefore does not apply to innovative new configurations such as the HSCT. Therefore, physics-based, preliminary design tools must be used to model the characteristics of advanced aircraft in conceptual sizing routines. In addition, the evaluation of the aircraft design space often requires the analysis of many configurations in order to assess the impact of design constraints and determine the attainable range of system level metrics, a process which is very time consuming in both modeling and computer run time.

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.

An evolving aircraft synthesis simulation environment which offers improvements to existing methods at multiple levels of a design process is described in this paper. As design databases become obsolete due to the introduction of new technologies and classes of vehicles and as sophisticated analysis codes are often too computationally expensive for iterative applications, the design engineer may find a lack of usable information needed for decision making. Within the environment developed in this paper, rapid sensitivity analysis is possible through a unique representation of the relationship between fundamental design variables and system objectives. The combined use of the Design of Experiments and Response Surface techniques provides the ability to form this design relationship among system variables and target values, which is termed design-oriented 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.

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.

The growth of international markets as well as business partnerships between U.S. and Asian-based firms has lead to an increased interest in an economically viable business jet capable of supersonic cruise and trans-Pacific range with one stop over (or non-stop trans-Atlantic range)1. Such an aircraft would reduce the travel time to these regions by as much as 50% by increasing cruise Mach number from roughly 0.85 to 2.0. In response to this interest, the 1996 AIAA / United Technologies / Pratt & Whitney Individual Undergraduate Design Competition has issued a Request for Proposal for the conceptual design of a supersonic cruise business jet. The design of this aircraft considered both performance and economic issues in the conceptual design phase. Through the use of Response Surface Methodology (RSM) and Design of Experiments (DoE) techniques, the aerodynamics of this vehicle were modeled and incorporated into an aircraft sizing code, FLOPS.

An integrated, multidisciplinary environment of a tactical aircraft platform has been created by leveraging the powerful capabilities of both MATLAB/Simulink and Numerical Propulsion System Simulation (NPSS). The overall simulation includes propulsion, power, and thermal management subsystem models, which are integrated together and linked to an air vehicle model and mission profile. The model has the capability of tracking temperatures and performance metrics and subsequently controlling characteristics of the propulsion and thermal management subsystems. The integrated model enables system-level trade studies involving the optimization of engine bleed and power extraction and thermal management requirements to be conducted. The simulation can also be used to examine future technologies and advanced thermal management architectures in order to increase mission capability and performance.

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.

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.

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 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.

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 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.

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 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).