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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.

Variable cycle engines (VCEs) hold promise as an enabling technology for supersonic business jet (SBJ) applications. Fuel consumption can potentially be minimized by modulating the engine cycle between the subsonic and supersonic phases of flight. The additional flexibility may also contribute toward meeting takeoff and landing noise and emissions requirements. Several different concepts have been and are currently being investigated to achieve variable cycle operation. The core-driven fan stage (CDFS) variable cycle engine is perhaps the most mature concept since an engine of this type flew in the USAF Advanced Tactical Fighter prototype program in the 1990s. Therefore, this type of VCE is of particular interest for potential commercial application. To investigate the potential benefits of a CDFS variable cycle engine, a parametric model is developed using the NASA Numerical Propulsion System Simulation (NPSS).

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.

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 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.

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.

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.

Recent market studies indicate a renewed interest for a quiet Supersonic Business Jet (SBJ). The success of such a program will be strongly dependent upon the achievement of stringent engine noise, emissions and fuel consumption goals. This paper demonstrates the use of advanced design methods to develop a parametric design space exploration environment which will be ultimately used for the identification of an engine concept capable of satisfying acoustic levels imposed by FAR part 36 (stage IV) and NOx and CO2 standards as stated in the 1996 ICAO. The engine performance is modeled through the use of Response Surface and Design of Experiments Techniques, enabling the designer/decision-maker to change initial engine parameter values to detect the effects of the responses in a time efficient manner. Engine performance and engine weight results are obtained through physics-based engine analysis codes developed by NASA.

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.

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 success of business jets like the Citation X, the fastest civil aircraft in use after the Concorde, highlights the need for speed to improve business and globalization. Currently, developing a supersonic business jet has many technical and economical impediments. These obstacles include sonic boom, emissions and noise requirements problems that are easily meet or do not exist for subsonic aircraft. A baseline aircraft, defined by an optimization process, is the starting point for this study. However, this baseline aircraft does not meet the sonic boom, emissions and noise requirements, which are very strict. Companion studies to this one indicate that it may be possible to meet emissions and noise requirements, but it is clear that technology infusion is necessary for the future viability of this aircraft concept to succeed.

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.

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.

The challenge of designing next-generation systems that meet goals for system effectiveness, environmental compatibility, and cost has grown to the point that traditional design methodologies are becoming ineffective. Increases in the analysis complexity required, the number of objectives and constraints to be evaluated, and the multitude of uncertainties in today’s design problems are primary drivers of this situation. A new environment for design has been formulated to treat this situation. It is viewed as a testbed, in which new techniques in such areas as design-oriented/physics-based analysis, uncertainty modeling, technology forecasting, system synthesis, and decision-making can be posed as hypotheses. Several recent advances in elements of this multidisciplinary environment, termed the Virtual Stochastic Life Cycle Design Environment, are summarized in this paper.

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.