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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.

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.

Affordable, reliable endo- and exoatmospheric transportation, for both the military and commercial sectors, grows in importance as the world grows smaller and space exploration and exploitation increasingly impact our daily lives. However, the impact of disciplinary, operational, and technological uncertainties inhibit the design of the requisite hypersonic vehicles, an inherently multidisciplinary and non-deterministic process. Without investigation, these components of design uncertainty undermine the designers’ decision-making confidence. In this paper, the authors propose a new probabilistic design method, using Bayesian Statistics techniques, which allows assessment of the impact of disciplinary uncertainty on the confidence in the design solution. The proposed development of a two-stage reusable launch vehicle configuration highlights the means to first quantify the fidelity of the disciplinary analysis tools utilized, then propagate such to the vehicle system level.

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.

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.

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.

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 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.