Aerospace Systems

D. Andrisani
Professor Andrisani presently has two major funded research areas. The first area, precision location of ground targets from airborne platforms, is funded by the National Imagery and Mapping Agency (NIMA) and the US Air Force X-45A Program Office at the Wright Aeronautical Laboratory (through an umbrella contract from Rosettex (a.k.a. SRI International). The second research area, air traffic management, is funded by Metron Aviation, Inc. and the e-Enterprise Center at Discovery Park. Professor Andrisani is currently funded from Metron Aviation Inc. to study the automatic determination of the intent of a commercial airline pilot flying in controlled airspace. This funding area, called "intent inference," represents a major new research thrust into the air traffic management area. Leveraging in part off this work, Professor Andrisani and Professors Mario Rotea, Thomas Carney, Michael Nolan and Alok Chaturvedi recently were awarded funding from Discovery Park to perform "Air Traffic Management Research for the 21st Century and Beyond."
B. Caldwell
W. A. Crossley

Professor Crossley's major research interests are in the area of design methodologies and optimization, with emphasis on the use of genetic algorithms for aerospace engineering design problems. Techniques like the genetic algorithm will allow optimization-like techniques to be applied in the conceptual phase of design, which traditionally has been dominated by qualitative or subjective decision making. There are two major areas of research being pursued by Professor Crossley and his students - genetic algorithm roles in aerospace design and optimization, and genetic algorithm methodology development. Other research topics related to aerospace design are also investigated.

Topology Design of Rotor Blades for Aerodynamic and Structural Concerns. This computational research effort strives to develop a rotor blade design strategy with the potential to improve the aerodynamic, structural, and dynamic performance of advanced rotorcraft. This work investigates the Genetic Algorithm (GA) as a means to combine aerodynamic and structural concerns for topology design of rotor blades. Inverse airfoil design and optimal airfoil design are receiving much attention in both industry and academia; the same holds true for structural optimization. The combination of the two concerns for topology design has not been fully addressed. A multidisciplinary approach combining structural and aerodynamic concerns for optimal topology design of rotor blades provides potential benefit to the rotorcraft design process. The aerodynamic optimization portion of this research was cited in the technical research highlights of the NASA Ames Research Center, Rotor Aeromechanics Branch for 1999. Contributions in the structural portion of the research have demonstrated capabilities for discrete (on/off) topology, most notably handing connectivity issues and performing design of sections under combinations of bending and torsion, that several authors had previously claimed were not possible.

Genetic Algorithm Issues for Optimal Smart Actuator Placement. This research is investigating approaches for smart actuator placement to provide aircraft maneuverability without requiring hinged flaps or other control surfaces. The effort supports many of the goals of the Multidisciplinary Design Optimization focus efforts in NASA's Aircraft Morphing program. Computational studies are being conducted to allow comparison and selection of appropriate techniques for posing and solving an actuator placement problem. The work began with a geometrically simple wing model, but the approaches identified during this research have been applied to complete aircraft configurations. The problem statement and algorithm application are being used at NASA Langley by researchers working on the Aircraft Morphing Program. Research in this area has been cited twice as technical highlights for the NASA Langley Multidisciplinary Optimization Branch; once in 1998 and once in 1999. Improved Satellite Constellation Design and Optimization. Improving satellite constellation design is of great interest to any users of satellite communication (e.g. cellular phones, television), location (e.g. global positioning system) and/or observation (e.g. weather). Many of today's satellite constellation designs rely on the "Walker Constellations," a series of designs developed in 1970, which have rarely been improved upon. These constellations make use of symmetric constellations with circular orbits. Using the genetic algorithm to search the constellation design space has begun to yield constellation designs not previously envisioned but with performance equal to or greater than comparable Walker or "streets of coverage" constellations. Research is ongoing for sparse coverage constellations, constellation build-up problems, multiobjective constellation concerns and elliptic orbit constellations. The Aerospace Corporation performs satellite constellation design for its US Air Force customers using the design techniques developed as part of this research. In one of these studies, a multiobjective GA approach was able to generate constellation designs that outperformed constellations that had been under development for several months. The GA was able to do this in a matter of days.

Development of a Genetic Algorithm for Conceptual Design of Aircraft. Air vehicle conceptual design appears to be a promising area for application of the genetic algorithm as an approach to help automate part of the design process. Because the GA-based approach to conceptual design helps to reduce the number of qualitative decisions needed from the design team, this appears to have great potential for application to aircraft design. Work has been extensively conducted for helicopters, some additional work has been conducted for high-speed VTOL rotorcraft (e.g. tilt-rotor and tilt-wing aircraft), and work is currently underway for fixed-wing aircraft. The Systems Analysis Branch at NASA Langley Research Center supports this research.

Methods to Assess Commercial Aircraft Technologies. Increasing competition in the commercial aircraft industry requires that airframe manufacturers be judicious with technology research and development efforts. Currently, technology development strategies for commercial aircraft appear to be lacking; this research presents a methodology to assess new technologies in terms of both cost and performance. This methodology encompasses technologies that can be applied to the aircraft design and technologies that improve the development, manufacturing, and testing of the aircraft. This differs from past studies that focused upon a small number of performance-based technologies. The method is divided into two phases. The first phase evaluates technologies based on cost measures alone. The second phase redesigns an aircraft with new technologies, assesses the relative importance of performance-based technologies, and recognizes technology interactions using Taguchi's Design of Experiments. For a wide-body transport aircraft example, the methodology identifies promising technologies for further study. Recommendations and conclusions about the methodology are made based on the results. This work was done in collaboration with the Configuration Engineering and Analysis group at Boeing Commercial Aircraft. Response Surface Methods as Approximation Models for Optimization. Approximation techniques, particularly the use of response surfaces (RS), have achieved wide popularity in engineering design optimization, especially for problems with computationally expensive analyses. The chief aims of using RS is to lower the cost of optimization and to smooth out the problem (e.g., for analyses solved iteratively, with a convergence tolerance). In one part of this research effort, an investigation of RS methods to minimize drag of a turbofan nacelle is being pursued in conjunction with engineers at Allison Advanced Development Company. This approach can improve the nacelle design practices at AADC by providing a formalized optimization framework for this CFD-based design exercise. The use of RS raises practical questions about the solution accuracy and computational expense. In particular, building response surfaces may involve a prohibitively large number of high-fidelity function evaluations, depending on problem dimensionality. In another part of this research effort, a computational study to address questions of expense and accuracy was undertaken with researchers in the Multidisciplinary Optimization Branch at NASA Langley Research Center. Important observations about the impact of constructing and using response surfaces for moderately high-dimensional problems were made. NASA researchers are using the RS models constructed during this portion of the research to further investigate techniques to manage approximation models in engineering optimization.

D. DeLaurentis

Dr. DeLaurentis’ research is motivated by the need for understanding the significant change in the structure and behavior of system design problems being faced by the aerospace community (and beyond), in particular where complex, interdisciplinary challenges persist. Many problems are increasingly recognized as being of “system-of-systems” type, consisting of multiple, heterogeneous, complex systems that are operate independently but have consequential interactions. The air transportation system is one example, as are numerous examples within the aerospace sector (and beyond). Such challenges require more than just the synthesis, design and fielding of new aerospace vehicles; they require the synthesis of capability networks that can adapt to evolving requirements and be robust to a variety of uncertainties. Thus, Dr. DeLaurentis has explored the use of network science, agent-based modeling, uncertainty representation and other approaches to address these multi-disciplinary, multi-system problems. In particular, the area of complex network theory is presently being explored to better account for interconnections among components and dynamic processes in designing future system-of-systems. The ultimate goal is to better define individual system requirements by understanding the context in which they will operate and to ensure that such operation will be robust over a wide range of plausible futures. This requires attention to dynamics in engineered systems, economics, policy, and operations dimensions. Through recent sponsored research from NASA, FAA, and private industry, Dr. DeLaurentis has developed and applied emerging research results, especially in air transportation and space exploration / transportation settings.

Dr. DeLaurentis seeks to build a community of researchers in these areas via active participation in professional societies. He is a Senior Member of the American Institute of Aeronautics and Astronautics (AIAA), the incoming Chairman of its Air Transportation Systems Technical Committee (TC) and a past-member of the Institute’s Multidisciplinary Design Optimization (MDO) TC. He is also a member of the IEEE, recently served as the Technical Program Co-Chair for the 2007 IEEE International Conference on System-of-Systems Engineering held in San Antonio TX, and is the new Co-Chair of Technical Committee on System of Systems for IEEE Systems, Man, and Cybernetics society.

I. Hwang
Dr. Hwang's research has been strongly motivated by difficult and interesting practical problems such as controlling multiple-vehicle systems. Controlling multiple-vehicle systems is one of the most important and challenging aspects of modern system theory and practice. Control of such systems involves the analysis of multiple dynamical systems which have inherently decentralized structures. The motions of vehicles have to be coordinated in such a way that the vehicles achieve their goals without conflicts between them. This requires path planning (computing optimal trajectories of vehicles from starting positions to destinations) and conflict detection and resolution. Path planning and conflict detection and resolution require information about individual vehicles, and therefore communication between vehicles for sharing this information is important. Multiple-vehicle systems encompass a variety of applications, including groups of mobile robots (e.g., UAS), ad-hoc sensor networks, and air traffic control. In addition, Dr. Hwang's research interests include control theory for hybrid and nonlinear systems, Unmanned Aircraft Systems, safety and security of Cyber-Physical Systems (e.g., aircraft, spacecraft, Air Traffic Control systems, and UAS), and space applications.
K. Marais
My research is multi-disciplinary in nature, spanning traditional engineering disciplines such as reliability, maintainability, and risk analysis, and extending to engineering economics (e.g., environmental impact of aviation and policy choices and implications) and organizational behavior (in particular in regard to system safety). The fundamental aim of my research is to guide better engineering decisions in system design and operation. To that end I perform research in three general areas:

System Safety and Risk Analysis
In this work, I investigate new ways of addressing the safety and risk challenges posed by complex systems. I am currently investigating the application of techniques from control theory and digital signal processing to risk analysis.

Systems Engineering Education
In this work, I investigate new ways of teaching systems engineering, from the sophomore to graduate student level.

Value-Centric System Design and Operation
In this work, I investigate system design and operation from the perspective of design impact on value. For example, recently my co-authors and I investigated the impact of reliability on system value and used our analysis to develop a method to identify optimal reliability levels that maximize system value delivery over time. I am now extending this perspective to system maintenance (an area with significant growth potential) and adapting this work to the civil aviation industry.

Civil Aviation Policy
In this work, I investigate various aspects of civil aviation policy. I focus on two areas. First, technology is seen as one of the primary enablers of increased air traffic over the next two decades. However, airlines and general aviation users are often reluctant to adopt new technologies. Using a value-centric approach I developed a framework that can be used to identify and address the causes of adoption reluctance and so increase the likelihood of successful technology transitions.

Second, the impact of aviation on the environment is receiving increasing attention. However, aviation environmental policies are usually evaluated in isolation or on a cost-effectiveness basis. Such evaluations do not take into account the complex interdependencies between aviation environmental effects (e.g., quieter engines may be heavier and therefore increase fuel consumption). Here, again, a value-centric perspective that takes into account both the benefits and costs of aviation can allow better policy decisions.
J. P. Sullivan
Current research interest is in the area of experimental aerodynamics with particular emphasis on comparison of experimental data with computational analysis. Work continues on developing instrumentation for shear stress measurement and pressure and temperature paint for: Wind tunnels - low speed to hypersonic, gas turbine engines and flight tests
D. Sun
My research areas include air traffic control, strategic traffic flow management, dynamic airspace configuration, and studies for Next Generation Air Transportation System (NextGen). I am interested in mathematical modeling and control of physical networked dynamical systems. Constraints are inherent to physical problems, yet they often make mathematical formulations hard to solve. I am interested in developing algorithms to solve these constrained optimization problems, in particular, algorithms to solve large scale problems that were beyond the reach of standard techniques. With an emphasis on aerospace engineering, I am interested in advancing the state of science in modeling and solution of stochastic, dynamic air traffic flow management problems, helping define and build the NextGen traffic flow management vision, philosophy, and architecture. I am also interested in implementing my algorithms on real-time platforms and building toolkits (software) for decision support. For air traffic control, the long term goal of the toolkit is the partial automation of some functions currently performed by humans, with the objective of improving safety and performance while easing workload.
T. A. Weisshaar
Primary research areas include optimization of structural concepts for smart aeroelastic structures and efficient multidisciplinary design. Currently, two primary areas are of interest:
  • Aeroelastic tailoring and active flexible wings. This includes using conventional articulated surfaces such as ailerons and leading edge devices for roll control, as well as using smart materials to change the camber of advanced wing concepts for aircraft control. Objectives also include aeroelastic design for reduced drag and optimization of smart wing flutter suppression systems for micro-air vehicles. We are also developing innovative techniques with advanced composite structure design to find optimal designs and reduce time to develop new concepts.
  • Design methodology. - developing new methods and algorithms to improve the ability of a design team to generate innovative, creative concepts for aerospace vehicles. This includes examining how the external aerodynamic and internal structural topology of lifting surfaces can be addressed simultaneously in the design process. This also includes introducing manufacturing concerns and decisions early in the design process and creating, through the early use of finite element models, more feed-forward/feed-back paths.
We have been examining how to use new modeling software to generate and present accurate, useful information to designers by displaying load paths and theoretically optimal designs. This leads to an improved conceptual design process for airplane structures that begins with a few participants and quickly proceeds to a high level with diverse technical groups represented. We are involved in the creation of an object-oriented system, using Adaptive Modeling Language (AML), to provide a natural, integrated, virtual environment for modeling, linking and simulating the aircraft design process from its earliest conceptual phase into preliminary design. When completed, this system will allow an integrated product team access to a virtual environment that scientifically simulates the iterative, collaborative process required to design an airplane in a short amount of time.