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The blade crossing event of a coaxial counter-rotating rotor is a potential source of noise and impulsive blade loads. Blade crossings occur many times during each rotor revolution. In previous research by the authors, this phenomenon was analyzed by simulating two airfoils passing each other at specified speeds and vertical separation distances, using the compressible Navier-Stokes solver OVERFLOW. The simulations explored mutual aerodynamic interactions associated with thickness, circulation, and compressibility effects. Results revealed the complex nature of the aerodynamic impulses generated by upper/lower airfoil interactions. In this paper, the coaxial rotor system is simulated using two trains of airfoils, vertically offset, and traveling in opposite directions. The simulation represents multiple blade crossings in a rotor revolution by specifying horizontal distances between each airfoil in the train based on the circumferential distance between blade tips.

Neural network augmented model inversion control is used to provide a civilian tilt-rotor aircraft with consistent response characteristics throughout its operating envelope, including conversion flight. The implemented response types are Attitude Command Attitude Hold in the longitudinal channel, and Rate Command Attitude Hold about the roll and yaw axes. This article describes the augmentation in the roll channel and the augmentation for the yaw motion including Heading Hold at low airspeeds and automatic Turn Coordination at cruise flight. Conventional methods require extensive gain scheduling with tilt-rotor nacelle angle and airspeed. A control architecture is developed that can alleviate this requirement and thus has the potential to reduce development time. It also facilitates the implementation of desired handling qualities, and permits compensation for partial failures.

The design of complex systems, such as commercial aircraft, has drastically changed since the middle 1970's. Budgetary and airline requirements have forced many aerospace companies to reduce the amount of time and monetary investments in future revolutionary concepts and design methods. The current NASA administration has noticed this shift in aviation focus and responded with the “Three Pillars for Success” program. This program is a roadmap for the development of research, innovative ideas, and technology implementation goals for the next 20 years. As a response to this program, the Aerospace Systems Design Laboratory at Georgia Tech is developing methods whereby forecasting techniques will aid in the proper assessment of future vehicle concepts. This method is called Technology Impact Forecasting (TIF). This method is applied to a medium-range, intra-continental, commercial transport concept.

This paper critically evaluates the use of Neural Networks (NNs) as metamodels for design applications. The specifics of implementing a NN approach are researched and discussed, including the type and architecture appropriate for design-related tasks, the processes of collecting training and validation data, and training the network, resulting in a sound process, which is described. This approach is then contrasted to the Response Surface Methodology (RSM). As illustrative problems, two equations to be approximated and a real-world problem from a Stability and Controls scenario, where it is desirable to predict the static longitudinal stability for a High Speed Civil Transport (HSCT) at takeoff, are presented. This research examines Response Surface Equations (RSEs) as Taylor series approximations, and explains their high performance as a proven approach to approximate functions that are known to be quadratic or near quadratic in nature.

An architecture is proposed for on-demand rapid commuting across congested-traffic areas. A lighter-than-air (LTA) vehicle provides the efficient loitering and part of the lift, while a set of cycloidal rotors provides the lift for payload as well as propulsion. This combination offers low noise and low downwash. A standardized automobile carriage is slung below the LTA, permitting driveway to driveway boarding and off-loading for a luxury automobile. The concept exploration is described, converging to the above system. The 6-DOF aerodynamic load map of the carriage is acquired using the Continuous-Rotation method in a wind tunnel. An initial design with rear ramp access is modified to have ramps at both ends. The initial design shows a divergence sped in access of 100 mph. An effort to improve the ride quality using yaw stabilizers, failed as the dynamic behavior becomes unstable. The requirements for control surfaces and instrumentation are discussed.

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.

An affordable technique is proposed for fast quantitative analysis of aerobatics and other complex flight domains of highly maneuverable aircraft. A generalized autonomous situational model of the “pilot (automaton) – vehicle – operational environment” system is employed as a “virtual test article”. Using this technique, a systematic knowledge of the system behavior in aerobatic flight can be generated on a computer, much faster than real time. This information can be analyzed via a set of knowledge mapping formats using a 3-D graphics visualization tool. Piloting and programming skills are not required in this process. Possible applications include: aircraft design and education, applied aerodynamics, flight control systems design, planning and rehearsal of flight test and display programs, investigation of aerobatics-related flight accidents and incidents, physics-based pilot training, research into new maneuvers, autonomous flight, and onboard AI.

A hybrid electric vehicle (HEV) simulation has been developed for an electric-assist parallel configuration vehicle, at the University of Tennessee, Knoxville. The model was developed in MATLAB/SIMULINK using ADVISOR, a HEV simulation model developed by the National Renewable Energy Laboratory. The Neon simulation model implements a power control strategy using throttle position as the primary input. It incorporates other features of HEV power control such as battery regeneration and regenerative braking. A practical way of battery modeling is incorporated into this model. The model also simulates the vehicle operation as a pure electric vehicle (EV) or as a conventional vehicle (heat engine only). By using the Neon model, the performance of the vehicle has been analyzed using parametric analysis of the vehicle components and power control parameters. Recommendations are given for improving the design based on the simulation results.

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.