Forecasting the post-bifurcation dynamics of large-dimensional slow-oscillatory systems using critical slowing down and center space reduction

Ghadami, Amin; Epureanu, Bogdan I.

doi:10.1007/s11071-016-3250-y

Cited by 22 publications

(2 citation statements)

References 31 publications

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“…Both numerical and experimental results were performed to test the effectiveness of the ARMA parametric model for aeroelastic flutter prediction of the airfoil model. In these works, [200][201][202][203][204][205] a novel method based on a critical slowing down was proposed for forecasting the bifurcation behaviors only from the much fewer observation data of the pre-bifurcation regime. Simulation results suggest that the proposed method can predict the post-bifurcation regime accurately.…”

Section: B Data-driven Prediction and Controlmentioning

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: B Data-driven Prediction and Controlmentioning

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

“…Van Nes and Scheffer [33] showed that, in six ecological models, recovery rates from small perturbations decrease as a regime shift was approached. For more on numerical and experimental approaches for detecting bifurcations before they occur by exploiting the critical slowing down phenomenon, we refer to Lim and Epureanu [34], Ghadami and Epureanu [35,36] and Van de Leemput et al [37].…”

Section: Alternative Measures and Topics For Future Researchmentioning

confidence: 99%

How to find simple nonlocal stability and resilience measures

Lundström

2018

Nonlinear Dyn

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Stability of dynamical systems is a central topic with applications in widespread areas such as economy, biology, physics and mechanical engineering. The dynamics of nonlinear systems may completely change due to perturbations forcing the solution to jump from a safe state into another, possibly dangerous, attractor. Such phenomena cannot be traced by the widespread local stability and resilience measures, based on linearizations, accounting only for arbitrary small perturbations. Using numerical estimates of the size and shape of the basin of attraction, as well as the systems returntime to the attractor after given a perturbation, we construct simple nonlocal stability and resilience measures that record a systems ability to tackle both large and small perturbations. We demonstrate our approach on the Solow-Swan model of economic growth, an electro-mechanical system, a stage-structured population model as well as on a highdimensional system, and conclude that the suggested measures detect dynamic behavior, crucial for a systems stability and resilience, which can be completely missed by local measures. The presented measures are also easy to implement on a standard laptop computer. We believe that our approach will constitute an important step toward filling a current gap in the literature by putting forward and explaining simple ideas and meth-N. L. P. Lundström (B) Department of Mathematics and Mathematical Statistics, Umeå University, 90187 Umeå, Sweden e-mail: niklas.lundstrom@umu.se ods, and by delivering explicit constructions of several promising nonlocal stability and resilience measures.

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Experimental Bifurcation Forecasting Using the Transient Response of an Airfoil in a Wind Tunnel

García Pérez,

Ghadami,

Sanches

et al. 2024

Conference Proceedings of the Society for Experimental Mechanics Series

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Forecasting the post-bifurcation dynamics of large-dimensional slow-oscillatory systems using critical slowing down and center space reduction

Cited by 22 publications

References 31 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

How to find simple nonlocal stability and resilience measures

Experimental Bifurcation Forecasting Using the Transient Response of an Airfoil in a Wind Tunnel

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