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An advanced flight control system, which has been demonstrated to compensate for unanticipated failures in military aircraft, is proposed for use in general aviation. The method uses inverse control to decouple the flight controls and to modify the handling qualities of the aircraft, while employing artificial neural networks in order to compensate for any modeling error. These errors can stem from any differences between the model and the actual aircraft. Therefore, they can include in-flight hardware failures, rendering the system fault tolerant and reducing the necessity for multiple levels of redundancy. The proposed system is verified in simulations for longitudinal flight and is shown to be able to track pilot-commanded velocity and flight path angle. Also, one example is presented for in-flight changes of the configurations (flap deployment) where the controller is shown to adapt rapidly to these changes without a need for compensation by the pilot.

The architecture and training of artificial neural networks are briefly described. Five applications of these networks to design and analysis problems are presented; three in aerodynamics and two in flight dynamics. The aerodynamics cases are those of a harmonically oscillating airfoil, a pitching delta wing, and airfoil design. The flight dynamic examples involve control of a super maneuver and a decoupled control case. It is demonstrated that highly nonlinear aerodynamic cases can be generalized with sufficient accuracy for design purposes. It is shown that although neural networks generalize well on the aerodynamic problems, they appear lacking comparable robustness in modeling dynamic systems. It is also shown that generalization appears to become weak outside of the training domain.

A short survey of wing tip geometries for drag reduction is presented. These devices have been divided into two broad categories of passive and active. The first category is made of fixed geometries, while the second group is made of those employing moving parts. The former group is further divided into planar and nonplanar designs. In every case, a brief explanation of the underlying logic is given. Altogether, more than fifteen completely different designs and over seventy references have been cited. Some of these designs, such as winglets, have been explored for many years and have proven to be very effective at reducing the induced drag at higher values of lift coefficient. Some others, such as wing tip turbines, have just begun to attract attention. Wing tip fuel tanks, not being solely employed for drag reduction, have not been included in this paper.

A comparative analysis has been performed on the Boeing 727-100 using three conceptual design codes. These programs were: The Aircraft Synthesis Program, ACSYNT, Advanced Aircraft Analysis, AAA, and RDS-Student. The objective of this study was to investigate differences in the conceptual design methodologies of these three programs. All three codes showed reasonable prediction of drag in the subsonic flow regime. However all three programs had difficulty predicting transonic drag rise characteristics. The principal cause was the inability to accurately predict the critical drag rise Mach number. Difficulties in estimating the shape of the drag rise curve, relative to the critical Mach number, also contributed to the errors in drag prediction. AAA and RDS-Student gave reasonable predictions of maximum lift coefficient. ACSYNT could not model the triple-slotted flap system on the 727-100. The three codes showed a consistent trend towards under-prediction of empty weight.

A scissor wing configuration, consisting of four adjustable wing surfaces, is compared with a comparable fixed wing baseline configuration. Wave drag, induced drag, viscous drag, thrust required, and gust loading are calculated for both configurations. The scissor wing is shown to have lower zero lift wave drag and higher total lift to drag ratios than the baseline. It is demonstrated that the scissor configurations' sweep can be programmed to keep the static margin fixed. Thrust required for both the fixed static margin case and a constant sweep angle case are presented with the scissor configuration requiring lower thrust levels. The gust loading ratio of the scissor wing to the baseline is also shown to be significantly less than 1.0 for sweep angles greater than 20 degrees.

The authors explore the possibility of designing the flap system on a given wing for enhanced Crow instability. The problem motivation in terms of increased traffic volume and increased safety is described. A brief review of the technical literature is given. An exploratory two-dimensional potential flow formulation is presented. A generic wing and flap combination is used for trade-off studies. The authors show that the frequency with which the flap-tip and the wing-tip vortex filaments swirl around each other can be tuned to match that which corresponds to the largest rate of amplitude growth in the wake. The extent of the analysis being two-dimensional, the authors suggest careful wind- or water-tunnel testing in three dimensions to validate the concept.

In nonlinear cases, the SDG method requires multidimensional search procedures. However, in linear cases only one-dimensional search procedures are required to identify the critical gust load conditions. In this study the application of the backpropagation ANN method as a multi-dimensional modeling tool has been proposed to model or identify the global and local extrema of one-dimensional gust load responses. The maximum and minimum response values of ramp-step input gust profiles were considered to investigate the ANN modeling capability and effectiveness. The actual SDG analysis for nonlinear cases was hypothesized to be performed over a large and sparse domain, therefore the ANN could be trained to quickly identify the region of the domain containing the global extrema. The SDG analysis, then, could be concentrated on a smaller region thereby reducing computation time.