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Relevant bibliographies by topics / Flutter Margin

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Journal articles

Academic literature on the topic 'Flutter Margin'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Flutter Margin"

1

Abbasi, A. A., and J. E. Cooper. "Statistical evaluation of flutter boundaries from flight flutter test data." Aeronautical Journal 113, no. 1139 (2009): 41–51. http://dx.doi.org/10.1017/s0001924000002761.

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AbstractA methodology is described that determines the statistical confidence bounds on the results from flight flutter tests: modal parameter estimates, flutter margin values and flutter speed estimates, without the need for Monte-Carlo simulation. The approach is based on least squares statistics and eigenvalue perturbation theory applied to the various stages of the analysis process, starting with frequency and damping estimation through to the flutter margin calculations. The technique is demonstrated upon a number of data sets from aeroelastic simulations of flight flutter tests.

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2

Zafari, E., MM Jalili, and A. Mazidi. "Analytical nonlinear flutter and sensitivity analysis of aircraft wings subjected to a transverse follower force." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 4 (2018): 1503–15. http://dx.doi.org/10.1177/0954410017754171.

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In the present study, the nonlinear aeroelastic and sensitivity analysis of high aspect ratio wings subjected to a transverse follower force are discussed. A nonlinear structural model of wings is extracted and coupled with an incompressible unsteady aerodynamic model. The governing equations of motions are obtained via Hamilton’s principle and Galerkin method. Utilizing the method of multiple-scales, analytical approximate flutter response of the system is obtained. For validation, the analytical solution is compared with numerical solution and good agreement is observed. The time history of the tip displacement and tip twist solution are plotted for different airspeeds. Effects of follower force and its spanwise location and also the wing geometric characteristics on the flutter margin are discussed. Moreover, flutter margin sensitivity to different design parameters is analyzed. Results indicate that increasing the wing chord makes the system unstable. Furthermore, according to the analytical solution, effects of the wing chord and mass per unit length on the flutter margins are more important than the other system parameters.

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3

Niblett, LL T. "The fundamentals of body-freedom flutter." Aeronautical Journal 90, no. 899 (1986): 373–77. http://dx.doi.org/10.1017/s0001924000015979.

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SummaryThe object of this paper is to uncover the nature of the destabilising coupling that is the major cause of body-freedom flutter and to see whether a simple cure for the flutter can be found. To do this frequency-coalesence theory is applied to a simple aircraft. It is shown that the aircraft is liable to flutter if it has a sweptforward wing and a positive ‘tail-off’ cg margin or a sweptback wing and a negative cg margin but a simple cure for the flutter does not appear to exist.

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4

Sudha, U. P. V., G. S. Deodhare, and K. Venkatraman. "A comparative assessment of flutter prediction techniques." Aeronautical Journal 124, no. 1282 (2020): 1945–78. http://dx.doi.org/10.1017/aer.2020.84.

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ABSTRACTTo establish flutter onset boundaries on the flight envelope, it is required to determine the flutter onset dynamic pressure. Proper selection of a flight flutter prediction technique is vital to flutter onset speed prediction. Several methods are available in literature, starting with those based on velocity damping, envelope functions, flutter margin, discrete-time Autoregressive Moving Average (ARMA) modelling, flutterometer and the Houbolt–Rainey algorithm. Each approach has its capabilities and limitations. To choose a robust and efficient flutter prediction technique from among the velocity damping, envelope function, Houbolt–Rainey, flutter margin and auto-regressive techniques, an example problem is chosen for their evaluation. Hence, in this paper, a three-degree-of-freedom model representing the aerodynamics, stiffness and inertia of a typical wing section is used(1). The aerodynamic, stiffness and inertia properties in the example problem are kept the same when each of the above techniques is used to predict the flutter speed of this aeroelastic system. This three-degree-of-freedom model is used to generate data at speeds before initiation of flutter, during flutter and after occurrence of flutter. Using these data, the above-mentioned flutter prediction methods are evaluated and the results are presented.

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5

Yang, Zhi Chun, and Ying Song Gu. "Robust Flutter Analysis of an Airfoil with Flap Freeplay Uncertainty." Advanced Materials Research 33-37 (March 2008): 1247–52. http://dx.doi.org/10.4028/www.scientific.net/amr.33-37.1247.

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Modern robust flutter method is an advanced technique for flutter margin estimation. It always gives the worst-case flutter speed with respect to potential modeling errors. Most literatures are focused on linear parameter uncertainty in mass, stiffness and damping parameters, etc. But the uncertainties of some structural nonlinear parameters, the freeplay in control surface for example, have not been taken into account. A robust flutter analysis approach in μ-framework with uncertain nonlinear operator is proposed in this study. Using describing function method the equivalent stiffness formulation is derived for a two dimensional wing model with freeplay nonlinearity in its flap rotating stiffness. The robust flutter margin is calculated for the two dimensional wing with flap freeplay uncertainty and the results are compared with that obtained with nominal parameter values. It is found that by considering the perturbation of freeplay parameter more conservative flutter boundary can be obtained, and the proposed method in μ-framework can be applied in flutter analysis with other types of concentrated nonlinearities.

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6

Torii, Hiroshi, and Yuji Matsuzaki. "Flutter Margin Evaluation for Discrete-Time Systems." Journal of Aircraft 38, no. 1 (2001): 42–47. http://dx.doi.org/10.2514/2.2732.

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7

MATSUDAIRA, Yasuaki, Hiroyuki NAKAGAWA, Hikaru YOSHIDA, and Hiromichi OBARA. "Supercavitation Hydrofoil Performance and Torsional Flutter Margin." Transactions of the Japan Society of Mechanical Engineers Series B 66, no. 648 (2000): 2079–86. http://dx.doi.org/10.1299/kikaib.66.648_2079.

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8

Corpas, J. L. Casado, and J. López Díez. "Flutter margin with non-linearities: Real-time prediction of flutter onset speed." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 222, no. 6 (2008): 921–29. http://dx.doi.org/10.1243/09544100jaero251.

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9

Saputra, Angga Dwi, and R. Wibawa Purabaya. "Prediction of Flutter Boundary Using Flutter Margin for The Discrete-Time System." Journal of Physics: Conference Series 1005 (April 2018): 012019. http://dx.doi.org/10.1088/1742-6596/1005/1/012019.

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10

Price, S. J., and B. H. K. Lee. "Evaluation and Extension of the Flutter-Margin Method for Flight Flutter Prediction." Journal of Aircraft 30, no. 3 (1993): 395–402. http://dx.doi.org/10.2514/3.56887.

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