Frequency-domain identification of time-varying systems for analysis and prediction of aeroelastic flutter (original) (raw)
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Identification of flutter parameters for a wing model
Journal of The Brazilian Society of Mechanical Sciences and Engineering, 2006
A flexible mounting system has been developed for flutter tests with rigid wings in wind tunnel. The two-degree-of-freedom flutter obtained with this experimental system can be described as the combination of structural bending and torsion vibration modes. Active control schemes for flutter suppression, using a trailing edge flap as actuator, can be tested using this experimental setup. Previously to the development of the control scheme, dynamic and aeroelastic characteristics of the system must be investigated. Experimental modal analysis is performed and modes shape and frequencies are determined. Then, wind tunnel tests are performed to characterize the flutter phenomenon, determining critical flutter speed and frequency. Frequency response functions are also obtained for the range of velocities below the critical one showing the evolution of pitch and plunge modes and the coupling tendency with increasing velocity. Pitch and plunge data obtained in the time domain during these tests are used to evaluate the ability of the Extended Eigensystem Realization Algorithm to identify flutter parameter with increasing velocity. The results of the identification process are demonstrated in terms of the evolution of frequency and damping of the modes involved in flutter.
Flutter Boundary Identification for Time-Domain Computational Aeroelasticity
AIAA Journal, 2007
Three time-domain damping/frequency/flutter identification techniques are discussed; namely, the moving-block approach, the least-squares curve-fitting method, and a system-identification technique using an autoregressive moving-average model of the aeroelastic system. These methods are evaluated for use with time-intensive computational aeroelastic simulations, represented by the aeroelastic transient responses of a double-wedge airfoil and three-dimensional wing in hypersonic flow. The responses are generated using the NASA Langley CFL3D computational aeroelastic code, in which the aerodynamic loads are computed from the unsteady Navier-Stokes equations. In general, the methods agree well. The system-identification technique, however, provided quick damping and frequency estimates with minimal response-record length. In the present case, the computational cost required to generate each aeroelastic transient was reduced by 75%. Finally, a flutter margin for discrete-time systems, constructed using the autoregressive moving-average approach, is evaluated for use in the hypersonic flow regime for the first time. For the binary-mode case, the flutter margin exhibited a linear correlation with dynamic pressure, minimizing the number of responses required to locate flutter. However, the flutter margin was not linear for the multimode system, indicating that it does not perform as expected in all cases.
New time-domain technique for flutter boundary identification
Dynamics Specialists Conference, 1992
A new methodology for flutter boundary identification in the time domain is presented. This technique is based on a single-input single-output deterministic ARMA model and an on-line parameter estimation procedure. It is capable of simultaneous identification of the aeroelastic modal parameters as well as the static offset term which represents the static deformation or state of the aeroelastic system. The capabilities of the method are illustrated by applying it to several examples, such as: damped free oscillations, a two degree of freedom NACA 64A010 airfoil in transonic flight, and a cantilevered rectangular wing in subsonic flow. Numerical implementations of the new methodology developed in this study demonstrates that it is a cost effective time-domain technique for flutter boundary identification. Nomenclature Denotes value at continuous time t. Denotes { x) at discrete time k. Nondimensional elastic axis location, measured from midchord AR coefficient Airfoil semichord (c 12) MA coefficient Estimated static aeroelastic deflection Estimated static aeroelastic deflection due to a d RMS estimation error for C due to random noise Young's modulus The i-th undamped natural frequency (= oi12n) The i-th damped natural frequency (= 0di12~)
Application of Approximate Unsteady Aerodynamics for Flutter Analysis
51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference<BR> 18th AIAA/ASME/AHS Adaptive Structures Conference<BR> 12th, 2010
A technique for approximating the modal aerodynamic influence coefficient (AIC) matrices by using basis functions has been developed. A process for using the resulting approximated modal AIC matrix in aeroelastic analysis has also been developed. The method requires the unsteady aerodynamics in frequency domain, and this methodology can be applied to the unsteady subsonic, transonic, and supersonic aerodynamics. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root locus et cetera. The unsteady aeroelastic analysis using unsteady subsonic aerodynamic approximation is demonstrated herein. The technique presented is shown to offer consistent flutter speed prediction on an aerostructures test wing (ATW) 2 and a hybrid wing body (HWB) type of vehicle configuration with negligible loss in precision. This method computes AICs that are functions of the changing parameters being studied and are generated within minutes of CPU time instead of hours. These results may have practical application in parametric flutter analyses as well as more efficient multidisciplinary design and optimization studies.
Identification of 18 Flutter Derivatives by Forced Vibration Tests : A New Experimental Rig
2009
The aeroelastic stability of line-like slender structures, e .g. wide-spanned bridges, is often verified by calculating a critical wind speed at which aeroelastic phe nom na like galloping, divergence and flutter occur. Therefore the aeroelastic properties of the des ire bridge deck section are needed and commonly determined in wind tunnel tests. Different methods, free and forced vibration testing, exist. A new experimental rig for forced vibration tests in t hree degrees of freedom, heave, pitch and surge motion, has been constructed at Ruhr-Universität Bochum. With this ne w rig harmonic oscillations in a wind-fixed coordinate system are feasible as well as experiments in a bridge deck-fixed coordinate system under an arbitrary angle of attack. A presentation of the mechanical design and the identification algorithm will be given. Results of wind tunnel experiments, identified flutter derivatives for three degrees of freedom, are presente d for a NACA 0020 airfoil and two bridge ...
Flight flutter testing and aeroelastic stability of aircraft
Aircraft Engineering and Aerospace Technology, 2007
Purpose-This paper sets out to provide a general review of the flight flutter test techniques utilized in aeroelastic stability flight testing of aircraft, and to highlight the key items involved in flight flutter testing of aircraft, by emphasizing all the main information processed during the flutter stability verification based on flight test data. Design/methodology/approach-Flight flutter test requirements are first reviewed by referencing the relevant civil and military specifications. Excitation systems utilized in flight flutter testing are overviewed by stating the relative advantages and disadvantages of each technique. Flight test procedures followed in a typical flutter flight testing are described for different air speed regimes. Modal estimation methods, both in frequency and time domain, used in flutter prediction are surveyed. Most common flight flutter prediction methods are reviewed. Finally, key considerations for successful flight flutter testing are noted by referencing the related literature. Findings-Online, real time monitoring of flutter stability during flight testing is very crucial, if the flutter character is not known a priori. Techniques such as modal filtering can be used to uncouple response measurements to produce simplified single degree of freedom responses, which could then be analyzed with less-sophisticated algorithms that are more able to run in real time. Frequency domain subspace identification methods combined with time-frequency multiscale wavelet techniques are considered as the most promising modal estimation algorithms to be used in flight flutter testing. Practical implications-This study gives concise but relevant information on the flight flutter stability verification of aircraft to practising engineers. The three important steps used in flight flutter testing-structural excitation, structural response measurement, and stability prediction-are introduced by presenting different techniques for each of the three important steps. Emphasis has been given to the practical advantages and disadvantages of each technique. Originality/value-This paper offers a brief practical guide to all key items involved in flight flutter stability verification of aircraft.
Aeroelastic modeling and stability analysis: A robust approach to the flutter problem
International Journal of Robust and Nonlinear Control
In this paper a general approach to address modeling of aeroelastic systems, with the final goal to apply µ analysis, is discussed. The chosen test bed is the typical section with unsteady aerodynamic loads, which enables basic modeling features to be captured and so extend the gained knowledge to practical problems treated with modern techniques. The aerodynamic operator has a non-rational dependence on the Laplace variable s and hence two formulations for the problem are available: frequency domain or state-space (adopting rational approximations). The study attempts to draw a parallel between the two consequent LFT modeling processes, emphasizing critical differences and their effect on the predictions obtained with µ analysis. A peculiarity of this twofold formulation is that aerodynamic uncertainties are inherently treated differently and therefore the families of plants originated by the possible LFT definitions are investigated. One of the main results of the paper is to propose a unified framework to address the robust modeling task, which enables the advantages of both the approaches to be retained. On the analysis side, the application of µ analysis to the different models is shown, emphasizing its capability to gain insight into the problem.
Aerospace
This article presents a modal correlation and update carried out on an aeroelastic wind tunnel demonstrator representing a conventional passenger transport aircraft. The aim of this work is the setup of a corresponding numerical model that is able to capture the flutter characteristics of a scaled aeroelastic model designed to investigate and experimentally validate active flutter suppression technologies. The work described in this paper includes different finite element modeling strategies, the results of the ground vibration test, and finally the strategies adopted for modal updating. The result of the activities is a three-dimensional hybrid finite element model that is well representative of the actual aeroelastic behavior identified during the wind tunnel test campaign and that is capable of predicting the flutter boundary with an error of 1.2%. This model will be used to develop active flutter suppression controllers, as well as to perform the sensitivity analyses necessary t...
Linear Models and Calculation of Aeroelastic Flutter
scientificbulletin.upb.ro
In this paper the authors present an improved aerodynamic model dedicated to analyzing the intricate phenomenon of aeroelastic flutter. The appropriate modelling of the real phenomenon is crucial, since the determination of the wave conditions (ie the wave ...
Damping Models in Aircraft Flutter Analyses
2020
This paper aims to introduce a first-principle-based viscoelastic damping formulation to be applied to aeroelastic systems describing highly flexible aircraft in order to critically assess its influence into linear flutter and response analyses.