Based on pilots' scanning data and discussions with pilots, general aviation flight instruments have been classified into three categories. The classification is related to the type of information presented, the way the information is used, and the pilot's role as a monitor and controller. Suggestions are made for modifying the instruments of one category to improve the information displayed such that when monitoring, the pilot can more quickly extract the information needed.

A summary of computational and experimental aeroelastic (AE) and aeroservoelastic (ASE) results for the Semi-Span Super-Sonic Transport (S 4 T) wind-tunnel model is presented. A broad range of analyses and multiple AE and ASE wind-tunnel tests of the S 4 T wind-tunnel model have been performed in support of the ASE element in the Supersonics Program, part of the NASA Fundamental Aeronautics Program. This paper is intended to be an overview of multiple papers that comprise a special S 4 T technical session. Along those lines, a brief description of the design and hardware of the S 4 T wind-tunnel model will be presented. Computational results presented include linear and nonlinear aeroelastic analyses, and rapid aeroelastic analyses using CFD-based reduced-order models (ROMs). A brief survey of some of the experimental results from two open-loop and two closed-loop wind-tunnel tests performed at the NASA Langley Transonic Dynamics Tunnel (TDT) will be presented as well.

An overview of NASA's High Speed Aeroservoelasticity (ASE) project is provided with a focus on recent computational aeroelastic analyses of a low-boom supersonic configuration developed by Lockheed-Martin and referred to as the N+2 configuration. The overview includes details of the computational models developed to date including a linear finite element model (FEM), linear unsteady aerodynamic models, structured/unstructured CFD grids, and CFD-based aeroelastic analyses. In addition, a summary of the work involving the development of aeroelastic Reduced-Order Models (ROMs) and the application of the CFL3D-ASE code that enables the inclusion of a control system within the CFL3Dv6 CFD code is presented.

A summary of NASA's High Speed Aeroservoelasticity (ASE) project is provided with a focus on a low-boom supersonic configuration developed by Lockheed-Martin and referred to as the N+2 configuration. The summary includes details of the computational models developed to date including a linear finite element model (FEM), linear unsteady aerodynamic models, structured and unstructured CFD grids, and discussion of the FEM development including sizing and structural constraints applied to the N+2 configuration. Linear results obtained to date include linear mode shapes and linear flutter boundaries. In addition to the tasks associated with the N+2 configuration, a summary of the work involving the development of AeroPropulsoServoElasticity (APSE) models is also discussed.

An important objective of the Semi-Span Super-Sonic Transport (S 4 T) wind tunnel model program was the demonstration of Flutter Suppression (FS), Gust Load Alleviation (GLA), and Ride Quality Enhancement (RQE). It was critical to evaluate the stability and robustness of these control laws analytically before testing them and experimentally while testing them to ensure safety of the model and the wind tunnel. MATLAB based software was applied to evaluate the performance of closed-loop systems in terms of stability and robustness. Existing software tools were extended to use analytical representations of the S 4 T and the control laws to analyze and evaluate the control laws prior to testing. Lessons were learned about the complex windtunnel model and experimental testing. The open-loop flutter boundary was determined from the closed-loop systems. A MATLAB/Simulink Simulation developed under the program is available for future work to improve the CPE process. This paper is one of a series of that comprise a special session, which summarizes the S 4 T wind-tunnel program. Nomenclature CLO = control law output CPE = controller performance evaluation FRF = frequency response function or frequency responses det = determinant G = open-loop plant FLAP = wing trailing edge control surface FLAPCOM = command to FLAP FLAPEXC = excitation to FLAP HT = horizontal tail HTCOM = command to HT HTEXC = excitation to HT IBMID15I = accelerometer located on the inboard middle section of the wing LTI = linear time invariant state-space representation of a system. MIMO = multi-input multi-output NIBAFTZ = nacelle inboard aft accelerometer in the z direction ! = dynamic pressure, psf RCV = ride control vane SISO = single-input single-output ! ! = time history of ith excitation to control surface ! ! = time history of ith control law output ! ! = time history of ith plant output ! ! = matrix of frequency responses of control law outputs to excitations ! ! = matrix of frequency responses of plant outputs to excitations σ = singular value Subscripts f = flutter

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