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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.

This new paper aims to extend the authors’ previous contributions about open-loop aircraft flutter test to closed-loop aircraft flutter test by virtue of the proposed direct data–driven strategy. After feeding back the output signal to the input and introducing one feedback controller in the adding feedback loop, two parts, i.e. unknown aircraft flutter model and unknown feedback controller, exist in this closed-loop aircraft flutter system, simultaneously, whose input and output are all corrupted with external noise. Because of the relations between aircraft flutter model parameters and the unknown aircraft model, direct data–driven identification is proposed to identify that aircraft flutter model, then some identification algorithms and their statistical analysis are given through the authors’ own derivations. As the feedback controller can suppress the aircraft flutter or guarantee the flutter response converge to one desired constant value, the direct data–driven control is applied to design that feedback controller only through the observed data sequence directly. Numerical simulation results have demonstrated the efficiency of the proposed direct data–driven strategy. Generally, during our new information age, direct data–driven strategy is widely applied around our living life.

First, consider one more complex closed loop stochastic aircraft flutter model, whose input–output are all corrupted with external noise. Second, for the identification problem of closed-loop aircraft flutter model parameters, new identification algorithm and some considerations are given to the corresponding direct data–driven identification. Third, to design that feedback controller, existing in that closed-loop aircraft flutter model, direct data–driven control is proposed to design the feedback controller, which suppresses the flutter response actively.

A novel direct data–driven strategy is proposed to achieve the dual missions, i.e. identification and control for closed-loop aircraft flutter test. First, direct data–driven identification is applied to identify that unknown aircraft flutter model being related with aircraft flutter model parameters identification. Second, direct data–driven control is proposed to design that feedback controller.

To the best of the authors’ knowledge, this new paper extends the authors’ previous contributions about open-loop aircraft flutter test to closed-loop aircraft flutter test by virtue of the proposed direct data–driven strategy. Consider the identification problem of aircraft flutter model parameters within the presented closed loop environment, direct data–driven identification algorithm is proposed to achieve the identification goal. Direct data–driven control is proposed to design the feedback controller, i.e. only using the observed data to design the feedback controller.

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.

The purpose of this paper is to introduce a novel method to study the flutter coupling mechanism of the twin-fuselage aircraft, which is becoming a popular transportation vehicle recently.

A new method of flutter mode indicator is proposed based on the principle of work and power, which is realized through energy accumulation of generalized force work on generalized coordinates, based on which flutter coupling mechanism of the twin-fuselage aircraft is studied using ground vibration test and computational fluid dynamics/computational solid dynamics method.

Verification of the proposed flutter mode indicator is provided, by which the flutter mechanism of the twin fuselage is found as the horizontal tail’s torsion coupled with its bending effect and the “frequency drifting” phenomenon of twin-fuselage aircraft is explained logically, highlighting the proposed method in this paper.

This paper proposed a new method of flutter mode indicator, which has advantages in flutter modes indexes reliability, clear physical meaning and results normalization. This study found the flutter coupling mechanism of twin-fuselage aircraft, which has important guiding significance to the development of twin-fuselage aircraft.

A low-cost but credible method of low-subsonic flutter analysis based on ground vibration test (GVT) results is presented. The purpose of this paper is a comparison of two methods of immediate flutter problem solution: JG2 – low cost software based on the strip theory in aerodynamics (STA) and V-g method of the flutter problem solution and ZAERO I commercial software with doublet lattice method (DLM) aerodynamic model and G method of the flutter problem solution. In both cases, the same sets of measured normal modes are used.

Before flutter computation, resonant modes are supplied by some non-measurable but existing modes and processed using the author’s own procedure. For flutter computation, the modes are normalized using the aircraft mass model. The measured mode orthogonalization is possible. The flutter calculation made by means of both methods are performed for the MP-02 Czajka UL aircraft and the Virus SW 121 aircraft of LSA category.

In most cases, both compared flutter computation results are similar, especially in the case of high aspect wing flutter. The Czajka T-tail flutter analysis using JG2 software is more conservative than the one made by ZAERO, especially in the case of rudder flutter. The differences can be reduced if the proposed rudder effectiveness coefficients are introduced.

The low-cost methods are attractive for flutter analysis of UL and light aircraft. The paper presents the scope of the low-cost JG2 method and its limitations.

In comparison with other works, the measured generalized masses are not used. Additionally, the rudder effectiveness reduction was implemented into the STA. However, Niedbal (1997) introduced corrections of control surface hinge moments, but the present work contains results in comparison with the outcome obtained by means of the more credible software.

IT is commonly held that today we are living in the age of the specialist. Within the aircraft industry, no one is more vulnerable to having this label of specialist thrust upon him than the flutter and vibration engineer, but I submit that far from having the narrow outlook which is taken to be the specialist's chief property, the flutter man has to be part stressman and part aerodynamicist; he must also have a working knowledge of the application of electronics to modern vibration test techniques and computing machinery, to say nothing of being part mathematician and, not least, part engineer, for we must not forget that after all, strange as it may seem at times to some of us, in the calm of our design offices, we are engaged in the engineering business.

The finite element model developed for a new-designed aircraft was used to solve some problems of structural dynamics. The key purpose of the task was to estimate the critical flutter velocities of the light airplane by performing numerical analysis with application of MSC Software.

Flutter analyses processed by Nastran require application of some complex aeroelastic model integrating two separate components – structural model and aerodynamic model. These sub-models are necessary for determining stiffness, mass and aerodynamic matrices, which are involved in the flutter equation. The aircraft structural model with its non-structural masses was developed in Patran. To determine the aerodynamic coefficient matrix, some simplified aerodynamic body-panel geometries were developed. The flutter equation was solved with the PK method.

The verified aircraft model was used to determine its normal modes in the range of 0-30 Hz. Then, some critical velocities of flutter were calculated within the range of operational velocities. As there is no certainty that the computed modes are in accordance with the natural ones, some parametric calculations are recommended. Modal frequencies depend on structural parameters that are quite difficult to identify. Adopting their values from the reasonable range, it is possible to assign the range of possible frequencies. The frequencies of rudder or elevator modes are dependent on their mass moments of inertia and rigidity of controls. The critical speeds of tail flutter were calculated for various combinations of stiffness or mass values.

The task described here is a preliminary calculational study of normal modes and flutter vibrations. It is necessary to prove the new airplane is free from flutter to fulfil the requirement considered in the type certification process.

The described approach takes into account the uncertainty of results caused by the indeterminacy of selected constructional parameters.

The effect of structural damping on panel flutter has received little treatment in the literature but the available information suggests that such an effect may be destabilizing. By considering a two‐dimensional, simply‐supported panel and using linear piston theory for the aerodynamic forces an analysis is presented in which the effect of hysteretic structural damping is considered. The main emphasis is on flat unbuckled panels, although a brief investigation of buckled panels is also presented, and it is concluded that there is an interdependence of structural and aerodynamic damping, which in the range of Mach numbers for which piston theory is valid, shows the destabilizing effect of structural damping. This effect is apparently more pronounced at high altitudes. A comprehensive bibliography of panel flutter is also included.

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.

Transonic flutter and active flap control, in two dimensions, are simulated by coupling independent structural dynamic and inviscid aerodynamic models, in the time domain. A flight control system, to actively control the trailing edge flap motion, has also been incorporated and, since this requires perfect synchronisation of fluid, structure and control signal, the “strong” coupling approach is adopted. The computational method developed is used to perform transonic aeroelastic and aeroservoelastic calculations in the time domain, and used to compute stability (flutter) boundaries of 2D wing sections. Open and closed loop simulations show that active control can successfully suppress flutter and results in a significant increase in the allowable speed index in the transonic regime. It is also shown that active control is still effective when there is free‐play in the control surface hinge. Flowfield analysis is used to investigate the nature of flutter and active control, and the fundamental importance of shock wave motion in the vicinity of the flap is demonstrated.