Stochastic stability and dynamics of a two-dimensional structurally nonlinear airfoil in turbulent flow

Singh, Prabhjot; Yeong, Hoong Chieh; Zhang, Huiqing; Rapti, Zoi; Namachchivaya, N. Sri

doi:10.1007/s11012-016-0445-8

Cited by 7 publications

(1 citation statement)

References 18 publications

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“…The stability of aeroelastic systems with random fluctuations is very crucial to engineering applications. Singh et al 129 explored stochastic stability of a typical two-dimensional airfoil aeroelastic model in turbulence flow. The Dryden turbulence models (5a)-(5b) were exploited to describe the vertical and longitudinal velocity components, and the Hopf bifurcation phenomenon was analyzed via a stochastic dimensional reduction method.…”

Section: Stochastic Stabilitymentioning

confidence: 99%

Complex nonlinear dynamics and vibration suppression of conceptual airfoil models: A state-of-the-art overview

Liu

Kurths

et al. 2022

Chaos: An Interdisciplinary Journal of Nonlinear Science

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During the past few decades, several significant progresses have been made in exploring complex nonlinear dynamics and vibration suppression of conceptual aeroelastic airfoil models. Additionally, some new challenges have arisen. To the best of the author’s knowledge, most studies are concerned with the deterministic case; however, the effects of stochasticity encountered in practical flight environments on the nonlinear dynamical behaviors of the airfoil systems are neglected. Crucially, coupling interaction of the structure nonlinearities and uncertainty fluctuations can lead to some difficulties on the airfoil models, including accurate modeling, response solving, and vibration suppression. At the same time, most of the existing studies depend mainly on a mathematical model established by physical mechanisms. Unfortunately, it is challenging and even impossible to obtain an accurate physical model of the complex wing structure in engineering practice. The emergence of data science and machine learning provides new opportunities for understanding the aeroelastic airfoil systems from the data-driven point of view, such as data-driven modeling, prediction, and control from the recorded data. Nevertheless, relevant data-driven problems of the aeroelastic airfoil systems are not addressed well up to now. This survey contributes to conducting a comprehensive overview of recent developments toward understanding complex dynamical behaviors and vibration suppression, especially for stochastic dynamics, early warning, and data-driven problems, of the conceptual two-dimensional airfoil models with different structural nonlinearities. The results on the airfoil models are summarized and discussed. Besides, several potential development directions that are worth further exploration are also highlighted.

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Section: Stochastic Stabilitymentioning

confidence: 99%

Complex nonlinear dynamics and vibration suppression of conceptual airfoil models: A state-of-the-art overview

Liu

Kurths

et al. 2022

Chaos: An Interdisciplinary Journal of Nonlinear Science

View full text Add to dashboard Cite

show abstract

Random dynamical systems: addressing uncertainty, nonlinearity and predictability

Namachchivaya

2016

Meccanica

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Dynamical responses of airfoil models with harmonic excitation under uncertain disturbance

Liu

Guo

et al. 2017

Nonlinear Dyn

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Stochastic stability and dynamics of a two-dimensional structurally nonlinear airfoil in turbulent flow

Cited by 7 publications

References 18 publications

Complex nonlinear dynamics and vibration suppression of conceptual airfoil models: A state-of-the-art overview

Complex nonlinear dynamics and vibration suppression of conceptual airfoil models: A state-of-the-art overview

Random dynamical systems: addressing uncertainty, nonlinearity and predictability

Dynamical responses of airfoil models with harmonic excitation under uncertain disturbance

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