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Traditional dynamic and flutter analysis demands a detailed finite element model of the aircraft in terms of its mass and stiffness distribution. However, in absence of these details, modal parameters obtained from experimental tests can be used to predict the flutter characteristics of an aircraft. The purpose of this paper is to develop an improved and reliable method to predict the flutter characteristics of an aircraft structure of unknown configuration under an anticipated aerodynamic loading using software such as MSC Nastran and experimental modal parameters (such as mode shapes, natural frequencies and damping) from ground vibration tests.

A finite element model with nodes representing the test points on the aircraft is created with appropriate boundary constraints. A direct matrix abstraction program has been written for NASTRAN software that carries out a normal modes analysis and replaces the mass normalized eigenvalues and vectors with the experimentally obtained modal parameters. The flutter analysis proceeds with the solution of the flutter equation in the flutter module of NASTRAN.

The method has been evaluated for a light composite aircraft and its results have been compared with flight flutter tests and the flutter speeds obtained from the finite element model with actual stiffness and mass distributions of the aircraft.

The methodology developed helps in the realistic prediction of flutter characteristics of a structure with known geometric configuration and does not need material properties, mass or stiffness distributions. However, experimental modal parameters of each configuration of the aircraft are required for flutter speed estimation.

The proposed methodology requires experimental modal parameters of each configuration of the aircraft for flutter speed estimation.

The paper shows that an effective method to predict flutter characteristics using modal parameters from ground vibration tests has been developed.

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.

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 is 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.

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.

This study gives concise but relevant information on the flight flutter stability verification of aircraft to the practicing engineer. 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.

This paper offers a brief practical guide to all key items involved in flight flutter stability verification of aircraft.

IN Part I wc saw how structural flexibility could introduce aerodynamic forces which might eventually lead to instability, or to the complete nullification of a desired aerodynamic effect. The phenomenon of flutter presents another problem in stability, but in this case an oscillatory instability is threatened. It must be realized at the outset that flutter is no mere resonance phenomenon such as the bad vibrations a motor‐car may exhibit at a particular engine speed. Flutter is a vibration in which energy is extracted from the airstrcam to help build up the amplitude, and a catastrophic failure can easily occur within a second of the start of the flutter.

An outline is given of the uses of flutter models as an aid to the designer in the avoidance of flutter. Details are given of the different types and methods of construction that are used for flutter models and of the various test facilities that are available for high speed and low speed tests. The procedure followed in the U.K. for flutter clearance of the full scale aircraft is described, and the value of the electronic flutter simulator in this field is discussed.

The purpose of this paper is to analyse the effects of morphing on the aeroelastic behaviour of unmanned aerial vehicle (UAV) wings to make an emphasis on the required aeroelastic tailoring starting from the conceptual design of the morphing mechanisms.

In this study, flutter and divergence characteristics of a fully morphing wing design were discussed to show the dilapidating effect of morphing on the related parameters. The morphing wings were intended to achieve a high efficiency at different flight phases; thus, various morphing concepts were integrated into a UAV wing structure. Although it is considered beneficial to have the morphing capabilities to avoid the failure due to a possible wear out in flutter and divergence parameters; it is necessary to include the aeroelastic analyses at the early design phases. This study utilizes a combination of a reduced order structural model and Theodorsen unsteady aerodynamic model as primary analyses tools for flutter and divergence. The analyses were conducted by using an in-house developed pk-algorithm coupled with a commercial finite element analysis (FEA) tool. This approach yielded a fast solution capacity because of the state-space form used.

Analyses conducted showed that transition between take-off, climb, cruise and loiter phases yield a change in the flutter and divergence speeds as high as 138 and 305 per cent, respectively.

The research showed that an extensive aeroelastic investigation was required for morphing wing designs to achieve a failure safe design.

The research intends to highlight the possible deteriorating effects on structural design of morphing UAV wings by focusing on the aeroelastic characteristics. In addition to that, fundamental morphing concepts are compared in terms of the order of magnitude of their deteriorating effects.

The purpose of this paper is to analyze the stability of aeroelastic systems using aeroelastic frequency response function (FRF).

The proposed technique determines the instability boundary of an aeroelastic system based on condition number (CN) of aeroelastic FRF matrix or directly from FRFs data.

Stability margins of typical section and hingeless helicopter rotor blade in the subsonic flow regimes (quasi‐steady and unsteady models) are determined using proposed techniques as two case studies.

The paper introduces a technique which is applicable not only when aerodynamic and structure analytical models are available but also when there are experimental models for structure and/or aerodynamics, such as impulse response functions data or FRFs data. In other words, the main advantage of the proposed method, besides its simplicity and low memory requirement, is its ability to utilize experimental data.

On the basis of certain simplifying assumptions a general equation can be developed that provides an estimate of the flutter speed of a binary system. The equation includes aerodynamic stiffness derivatives, and in the absence of reliable derivatives for oscillatory motion it is suggested that derivatives derived from steady flow measurements can be used. The equation is applied to derive specific formulae for main surface flexure‐torsion flutter. The effects of compressibility on the derivatives for this particular case is deduced, and the derivatives are then used to estimate certain general effects of compressibility on flutter. It appears that many of the generally accepted features of flutter in the transonic region can be established by this approach, but the application of the formula is limited by the lack of reliable data for aerodynamic stiffness derivatives. A concentrated effort to establish these derivative values is likely to be more rewarding in the long run than flutter tests on innumerable models to establish overall flutter trends of limited application.

Ground vibration testing (GVT) results can be used as system parameters for predicting flutter, which is essential for aeroelastic clearance. This paper aims to compute GVT-based flutter in time domain, using unsteady air loads by matrix polynomial approximations.

The experimental parameters, namely, frequencies and mode shapes are interpolated to build an equivalent finite element model. The unsteady aerodynamic forces extracted from MSC NASTRAN are approximated using matrix polynomial approximations. The system matrices are condensed to the required shaker location points to build an aeroelastic reduced order state space model in SIMULINK.

The computed aerodynamic forces are successfully reduced to few input locations (optimal) for flutter simulation on unknown structural system (where stiffness and mass are not known) through a case study. It is demonstrated that GVT data and the computed unsteady aerodynamic forces of a system are adequate to represent its aeroelastic behaviour.

Airforce of every nation continuously upgrades its fleet with advanced weapon systems (stores), which demands aeroelastic flutter clearance. As the original equipment manufacturers does not provide the design data (stiffness and mass) to its customers, a new methodology to build an aeroelastic system of unknown aircraft is devised.

A hybrid approach is proposed, involving GVT data to build an aeroelastic state space system, using rationally approximated air loads (matrix polynomial approximations) computed on a virtual FE model for ground flutter simulation.

The purpose of this paper is to present a novel approach in aeroservoelastic analysis and robust control of a wing section with two control surfaces in leading‐edge and trailing‐edge. The method demonstrates how the number of model uncertainties can affect the flutter margin.

The proposed method effectively incorporates the structural model of a wing section with two degrees of freedom of pitch and plunge with two control surfaces on trailing and leading edges. A quasi‐steady aerodynamics assumption is made for the aerodynamic modeling. Basically, perturbations are considered for the dynamic pressure models and uncertainty parameters are associated with structural stiffness and structural damping and are accounted for in the model by a Linear Fractional Transformation (LFT) model. The control commands are applied to a first and second order electro‐mechanical actuator.

Dynamic performance of aeroelastic/aeroservoelastic system including time responses, system modal specifications, critical flutter speeds, and stability margins are extracted and compared with each other. Simulation results are validated through experiments and are compared to other existing methods available to the authors. Results of simulations with four structural uncertainties and first order controllers have a good agreement with experimental test results. Furthermore, it is shown that by using a high gain second order controller, the aeroservoelastic (ASE) system does not have any coupling nature in frequency response.

In this study, modeling, simulation, and robust control of a wing section have been investigated utilizing the μ‐Analysis method and the wing flutter phenomenon is predicted in the presence of multiple uncertainties. The proposed approach is an advanced method compared to conventional flutter analysis methods (such as V‐g or p‐k) for calculating stability margin of aeroelastic/aeroservoelastic systems.

The purpose of this paper is to find an influence of the reduced stiffness of actuators, located on the most outer parts of ailerons, flaperons, rudders, elevators and elevons on the excitation of flutter. This phenomenon is especially important for unmanned aerial vehicles because they continuously use all these control surfaces for trimming and stabilisation and on the other hand, the numerous statistics show that failure of elements of flight control systems are still the most probable reasons of aircraft critical failure.

Flutter calculations were performed by use of the classical modal approach. The normal vibrations of the free aircraft were measured in the ground vibration test (GVT). Test results were used either for verification of the FEM model of the structure – in this case for flutter calculation the MSC.Nastran software was used, or directly for flutter calculation. Based on the flutter analysis, the control surfaces critical for flutter were determined.

These so‐called critical control surfaces –, i.e. surfaces responsible for flutter excitation at first – are localized on outer parts of wing and empennage. It was found that the critical surfaces should have been mass balanced or should be irreversible. In the second case, i.e. when the control surfaces are irreversible, the actuators and drivers should have been of a high reliability, because disconnection of these elements could involve flutter.

This approach within the computational analysis is limited to linear case, otherwise NASTRAN software cannot be used for flutter analysis. GVTs could be performed successfully independently if the structure has linear or non‐linear properties.

It was found that before any flight the stiffness in the flight control system of all control surfaces must carefully be checked and kept above the critical stiffness value. Safety level strongly depends on the reliability of actuators used on such unmanned aerial vehicles. The simulation of disconnection (as a result of damage) of selected control surfaces is possible even if the GVT were provided on undamaged vehicle. To do it, the rotational mode of so‐called “free control surface” should be prepared (as an artificial resonant mode) for all deflected control surfaces; next all the resonant modes should be orthogonalized, relative to this artificial control surfaces mode.

This paper was based on two big European and national projects, and all presented results are original and were never published before. Some selected graphs were shown during the EASN Workshop, Paris, September 2010 at the presentation entitled: “Aeroelastic analysis of remotely controlled research vehicles with numerous control surfaces”.