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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.

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.

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.

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.

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.

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 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.

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.

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.

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.

One of the most essential contributors in the aircraft sizing and synthesis process is the creation and utilization of accurate drag polars. An improved general procedure to generate drag polars for conceptual and preliminary design purposes in the form of Response Surface Equations is outlined and discussed in this paper. This approach facilitates and supports aerospace system design studies as well as Multi-disciplinary Analysis and Optimization. The analytically created Response Surface Equations replace the empirical aerodynamic relations or historical data found in sizing and synthesis codes, such as the Flight Optimization System (FLOPS). These equations are commonly incorporated into system level studies when a configuration falls beyond the conventional realm. The approach described here is a statistics-based methodology, which combines the use of Design of Experiments and Response Surface Method (RSM).

Creation and utilization of accurate drag polars is essential in the aircraft sizing and synthesis process. Existing sizing and synthesis codes are based on historical data and cannot capture the aerodynamics of a non-conventional aircraft at the conceptual design phase. The fidelity of the aerodynamic analysis should be enhanced to increase the designer’s confidence in the results. Hence, there is need for a physics-based approach to generate the drag polars of an aircraft lying outside the conventional realm. The deficiencies of the legacy codes should be removed and replaced with higher fidelity meta-model representations. This is facilitated with response surface methodology (RSM), which is a mathematical and statistical technique that is suited for the modeling and analysis of problems in which the responses, the drag coefficients in this case, are influenced by several variables. The geometric input variables are chosen so that they represent a multitude of configurations.