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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Aeroservoelastic Modeling and Validation of a Thrust-Vectoring F/A-18 Aircraft

An F/A-18 aircraft was modified to perform flight research at high angles of attack (AOA) using thrust vectoring and advanced control law concepts for agility and performance enhancement and to provide a testbed for the computational fluid dynamics community. Aeroservoelastic (ASE) characteristics had changed considerably from the baseline F/A-18 aircraft because of structural and flight control system amendments, so analyses and flight tests were performed to verify structural stability at high AOA. Detailed actuator models that consider the physical, electrical, and mechanical elements of actuation and its installation on the airframe were employed in the analysis to accurately model the coupled dynamics of the airframe, actuators, and control surfaces. This report describes the ASE modeling procedure, ground test validation, flight test clearance, and test data analysis for the reconfigured F/A-18 aircraft. Multivariable ASE stability margins are calculated from flight data and compared to analytical margins. Because this thrust-vectoring configuration uses exhaust vanes to vector the thrust, the modeling issues are nearly identical for modem multi-axis nozzle configurations. This report correlates analysis results with flight test data and makes observations concerning the application of the linear predictions to thrust-vectoring and high-AOA flight.

Brenner, Martin J.↗
NASA NTRS1997

Wavelet Analyses of F/A-18 Aeroelastic and Aeroservoelastic Flight Test Data

Time-frequency signal representations combined with subspace identification methods were used to analyze aeroelastic flight data from the F/A-18 Systems Research Aircraft (SRA) and aeroservoelastic data from the F/A-18 High Alpha Research Vehicle (HARV). The F/A-18 SRA data were produced from a wingtip excitation system that generated linear frequency chirps and logarithmic sweeps. HARV data were acquired from digital Schroeder-phased and sinc pulse excitation signals to actuator commands. Nondilated continuous Morlet wavelets implemented as a filter bank were chosen for the time-frequency analysis to eliminate phase distortion as it occurs with sliding window discrete Fourier transform techniques. Wavelet coefficients were filtered to reduce effects of noise and nonlinear distortions identically in all inputs and outputs. Cleaned reconstructed time domain signals were used to compute improved transfer functions. Time and frequency domain subspace identification methods were applied to enhanced reconstructed time domain data and improved transfer functions, respectively. Time domain subspace performed poorly, even with the enhanced data, compared with frequency domain techniques. A frequency domain subspace method is shown to produce better results with the data processed using the Morlet time-frequency technique.

Martin J Brenner↗
NASA NTRS1997

STARS: An Integrated, Multidisciplinary, Finite-Element, Structural, Fluids, Aeroelastic, and Aeroservoelastic Analysis Computer Program

A multidisciplinary, finite element-based, highly graphics-oriented, linear and nonlinear analysis capability that includes such disciplines as structures, heat transfer, linear aerodynamics, computational fluid dynamics, and controls engineering has been achieved by integrating several new modules in the original STARS (STructural Analysis RoutineS) computer program. Each individual analysis module is general-purpose in nature and is effectively integrated to yield aeroelastic and aeroservoelastic solutions of complex engineering problems. Examples of advanced NASA Dryden Flight Research Center projects analyzed by the code in recent years include the X-29A, F-18 High Alpha Research Vehicle/Thrust Vectoring Control System, B-52/Pegasus Generic Hypersonics, National AeroSpace Plane (NASP), SR-71/Hypersonic Launch Vehicle, and High Speed Civil Transport (HSCT) projects. Extensive graphics capabilities exist for convenient model development and postprocessing of analysis results. The program is written in modular form in standard FORTRAN language to run on a variety of computers, such as the IBM RISC/6000, SGI, DEC, Cray, and personal computer; associated graphics codes use OpenGL and IBM/graPHIGS language for color depiction. This program is available from COSMIC, the NASA agency for distribution of computer programs.

Gupta, K. K.↗
NASA NTRS1999

Aeroservoelastic and Flight Dynamics Analysis Using Computational Fluid Dynamics

This document in large part is based on the Masters Thesis of Cole Stephens. The document encompasses a variety of technical and practical issues involved when using the STARS codes for Aeroservoelastic analysis of vehicles. The document covers in great detail a number of technical issues and step-by-step details involved in the simulation of a system where aerodynamics, structures and controls are tightly coupled. Comparisons are made to a benchmark experimental program conducted at NASA Langley. One of the significant advantages of the methodology detailed is that as a result of the technique used to accelerate the CFD-based simulation, a systems model is produced which is very useful for developing the control law strategy, and subsequent high-speed simulations.

Arena, Andrew S., Jr.↗
NASA NTRS2000

Pilot Comments From the Boeing High Speed Research Aircraft, Cycle 3, Simulation Study of the Effects of Aeroservoelasticity (LaRC.3)

This is a compilation of pilot comments from the Boeing High Speed Research Aircraft, Cycle 3, simulation study (LaRC.3) of the effects of aeroservoelasticity, conducted from October to December 1997 at NASA Langley Research Center. This simulation study was conducted using the Visual Motion Simulator. The comments are from direct tape transcriptions and have been edited for spelling only. These comments were made on tape following the completion of each flight card, immediately after the pilot was satisfied with his practice and data recording runs. Six pilots were used in the evaluation and they are identified as pilots A through F.

Bailey, Melvin L.↗
NASA NTRS2002

Scaling Laws Applied to a Modal Formulation of the Aeroservoelastic Equations

A method of scaling is described that easily converts the aeroelastic equations of motion of a full-sized aircraft into ones of a wind-tunnel model. To implement the method, a set of rules is provided for the conversion process involving matrix operations with scale factors. In addition, a technique for analytically incorporating a spring mounting system into the aeroelastic equations is also presented. As an example problem, a finite element model of a full-sized aircraft is introduced from the High Speed Research (HSR) program to exercise the scaling method. With a set of scale factor values, a brief outline is given of a procedure to generate the first-order aeroservoelastic analytical model representing the wind-tunnel model. To verify the scaling process as applied to the example problem, the root-locus patterns from the full-sized vehicle and the wind-tunnel model are compared to see if the root magnitudes scale with the frequency scale factor value. Selected time-history results are given from a numerical simulation of an active-controlled wind-tunnel model to demonstrate the utility of the scaling process.

Pototzky, Anthony S.↗
NASA NTRS2006

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Silva, Walter A.↗
NASA NTRS2007

Plans and Status of Wind-Tunnel Testing Employing an Aeroservoelastic Semispan Model

This paper presents the research objectives, summarizes the pre-wind-tunnel-test experimental results to date, summarizes the analytical predictions to date, and outlines the wind-tunnel-test plans for an aeroservoelastic semispan wind-tunnel model. The model is referred to as the Supersonic Semispan Transport (S4T) Active Controls Testbed (ACT) and is based on a supersonic cruise configuration. The model has three hydraulically-actuated surfaces (all-movable horizontal tail, all-movable ride control vane, and aileron) for active controls. The model is instrumented with accelerometers, unsteady pressure transducers, and strain gages and will be mounted on a 5-component sidewall balance. The model will be tested twice in the Langley Transonic Dynamics Tunnel (TDT). The first entry will be an "open-loop" model-characterization test; the second entry will be a "closed-loop" test during which active flutter suppression, gust load alleviation and ride quality control experiments will be conducted.

Perry, Boyd, III↗
NASA NTRS2007

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Walter A. Silva↗
NASA NTRS2008

Aeroservoelastic Stability Analysis of the X-43A Stack

The first air launch attempt of an X-43A stack, consisting of the booster, adapter and Hyper-X research vehicle, ended in failure shortly after the successful drop from the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) B-52B airplane and ignition of the booster. The stack was observed to begin rolling and yawing violently upon reaching transonic speeds, and the grossly oscillating fins of the booster separated shortly thereafter. The flight then had to be terminated with the stack out of control. Very careful linear flutter and aeroservoelastic analyses were subsequently performed as reported herein to numerically duplicate the observed instability. These analyses properly identified the instability mechanism and demonstrated the importance of including the flight control laws, rigid-body modes, structural flexible modes and control surface flexible modes. In spite of these efforts, however, the predicted instability speed remained more than 25 percent higher than that observed in flight. It is concluded that transonic shock phenomena, which linear analyses cannot take into account, are also important for accurate prediction of this mishap instability.

Pak, Chan-gi↗
NASA NTRS2008

Object-Oriented MDAO Tool with Aeroservoelastic Model Tuning Capability

An object-oriented multi-disciplinary analysis and optimization (MDAO) tool has been developed at the NASA Dryden Flight Research Center to automate the design and analysis process and leverage existing commercial as well as in-house codes to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic and hypersonic aircraft. Once the structural analysis discipline is finalized and integrated completely into the MDAO process, other disciplines such as aerodynamics and flight controls will be integrated as well. Simple and efficient model tuning capabilities based on optimization problem are successfully integrated with the MDAO tool. More synchronized all phases of experimental testing (ground and flight), analytical model updating, high-fidelity simulations for model validation, and integrated design may result in reduction of uncertainties in the aeroservoelastic model and increase the flight safety.

Pak, Chan-gi↗
NASA NTRS2010

Incorporation of SemiSpan SuperSonic Transport (S4T) Aeroservoelastic Models into SAREC-ASV Simulation

The Simulink-based Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV) was modified to incorporate linear models representing aeroservoelastic characteristics of the SemiSpan SuperSonic Transport (S4T) wind-tunnel model. The S4T planform is for a Technology Concept Aircraft (TCA) design from the 1990s. The model has three control surfaces and is instrumented with accelerometers and strain gauges. Control laws developed for wind-tunnel testing for Ride Quality Enhancement, Gust Load Alleviation, and Flutter Suppression System functions were implemented in the simulation. The simulation models open- and closed-loop response to turbulence and to control excitation. It provides time histories for closed-loop stable conditions above the open-loop flutter boundary. The simulation is useful for assessing the potential impact of closed-loop control rate and position saturation. It also provides a means to assess fidelity of system identification procedures by providing time histories for a known plant model, with and without unmeasured turbulence as a disturbance. Sets of linear models representing different Mach number and dynamic pressure conditions were implemented as MATLAB Linear Time Invariant (LTI) objects. Configuration changes were implemented by selecting which LTI object to use in a Simulink template block. A limited comparison of simulation versus wind-tunnel results is shown.

Christhilf, David M.↗
NASA NTRS2011

Aeroservoelastic Wind-Tunnel Tests of a Free-Flying, Joined-Wing SensorCraft Model for Gust Load Alleviation

A team comprised of the Air Force Research Laboratory (AFRL), Boeing, and the NASA Langley Research Center conducted three aeroservoelastic wind-tunnel tests in the Transonic Dynamics Tunnel to demonstrate active control technologies relevant to large, exible vehicles. In the first of these three tests, a full-span, aeroelastically scaled, wind-tunnel model of a joined-wing SensorCraft vehicle was mounted to a force balance to acquire a basic aerodynamic data set. In the second and third tests, the same wind-tunnel model was mated to a new, two-degree-of-freedom, beam mount. This mount allowed the full-span model to translate vertically and pitch. Trimmed flight at -10% static margin and gust load alleviation were successfully demonstrated. The rigid body degrees of freedom required that the model be own in the wind tunnel using an active control system. This risky mode of testing necessitated that a model arrestment system be integrated into the new mount. The safe and successful completion of these free-flying tests required the development and integration of custom hardware and software. This paper describes the many systems, software, and procedures that were developed as part of this effort. The balance and free ying wind-tunnel tests will be summarized. The design of the trim and gust load alleviation control laws along with the associated results will also be discussed.

Scott, Robert C.↗
NASA NTRS2015

Aeroservoelastic Wind-Tunnel Test of the SUGAR Truss Braced Wing Wind-Tunnel Model

The Subsonic Ultra Green Aircraft Research (SUGAR) Truss-Braced Wing (TBW) aeroservoelastic (ASE) wind-tunnel test was conducted in the NASA Langley Transonic Dynamics Tunnel (TDT) and was completed in April, 2014. The primary goals of the test were to identify the open-loop flutter boundary and then demonstrate flutter suppression. A secondary goal was to demonstrate gust load alleviation (GLA). Open-loop flutter and limit cycle oscillation onset boundaries were identified for a range of Mach numbers and various angles of attack. Two sets of control laws were designed for the model and both sets of control laws were successful in suppressing flutter. Control laws optimized for GLA were not designed; however, the flutter suppression control laws were assessed using the TDT Airstream Oscillation System. This paper describes the experimental apparatus, procedures, and results of the TBW wind-tunnel test. Acquired system ID data used to generate ASE models is also discussed.2 study.

Scott, Robert C.↗
NASA NTRS2016

Model Order Reduction of Aeroservoelastic Model of Flexible Aircraft

This paper presents a holistic model order reduction (MOR) methodology and framework that integrates key technological elements of sequential model reduction, consistent model representation, and model interpolation for constructing high-quality linear parameter-varying (LPV) aeroservoelastic (ASE) reduced order models (ROMs) of flexible aircraft. The sequential MOR encapsulates a suite of reduction techniques, such as truncation and residualization, modal reduction, and balanced realization and truncation to achieve optimal ROMs at grid points across the flight envelope. The consistence in state representation among local ROMs is obtained by the novel method of common subspace reprojection. Model interpolation is then exploited to stitch ROMs at grid points to build a global LPV ASE ROM feasible to arbitrary flight condition. The MOR method is applied to the X-56A MUTT vehicle with flexible wing being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies demonstrated that relative to the fullorder model, our X-56A ROM can accurately and reliably capture vehicles dynamics at various flight conditions in the target frequency regime while the number of states in ROM can be reduced by 10X (from 180 to 19), and hence, holds great promise for robust ASE controller synthesis and novel vehicle design.

aeroelasticity↗
NASA NTRS2016

A Status Review of the Commercial Supersonic Technology (CST) Aeroservoelasticity (ASE) Project

An overview of recent progress regarding the computational aeroelastic and aeroservoelastic (ASE) analyses of a low-boom supersonic configuration is presented. The overview includes details of the computational models developed to date with a focus on unstructured CFD grids, computational aeroelastic analyses, sonic boom propagation studies that include static aeroelastic effects, and gust loads analyses. In addition, flutter boundaries using aeroelastic Reduced-Order Models (ROMs) are presented at various Mach numbers of interest. Details regarding a collaboration with the Royal Institute of Technology (KTH, Stockholm, Sweden) to design, fabricate, and test a full-span aeroelastic wind-tunnel model are also presented.

Silva, Walter A.↗