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  Early warning of noise-induced catastrophic high-amplitude oscillations in an airfoil model

Ma, J., Liu, Q., Xu, Y., Kurths, J. (2022): Early warning of noise-induced catastrophic high-amplitude oscillations in an airfoil model. - Chaos, 32, 3, 033119.
https://doi.org/10.1063/5.0084796

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 Urheber:
Ma, Jinzhong1, Autor
Liu, Qi1, Autor
Xu, Yong1, Autor
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Noise-induced tipping from a low-amplitude oscillation state to a high-amplitude one is widespread in airfoil systems. Its occurrence may cause fatigue damage to the wing structure of an aircraft, which directly threatens its flight safety. Therefore, it is of utmost importance to predict the occurrence of noise-induced high-amplitude oscillations as the system parameters vary in airfoil systems. Taking a two-degrees-of-freedom airfoil model with random loadings as a prototype class of real systems, the prediction of noise-induced tipping from low-amplitude to high-amplitude oscillations is carried out in the present study. First, we analyze the effects of random fluctuations on the system response. The results show that noise-induced catastrophic high-amplitude oscillations take place before the bifurcation point of the corresponding deterministic airfoil model. Subsequently, the possibility that the low-amplitude oscillation state of the given noisy model jumps to the high-amplitude one is analyzed based on the escape probability. Then, the new concept of the high-risk region is defined. This is an efficient early warning indicator to approximately quantify the ranges of the system parameters where noise-induced high-amplitude oscillations may occur. Compared with the existing early warning indicators, this method is a non-local universal concept of stability. More importantly, it may provide theoretical guidance for aircraft designers to take some measures to avoid such catastrophic critical jump phenomena in practical engineering applications. Random fluctuations in a flight environment can induce tipping from a low-amplitude oscillation state to a high-amplitude one of an airfoil system. These typically undesirable high-amplitude oscillations often lead to airfoil structural damage, thereby increasing the risk of flight safety issues such as the aircraft breaking up in mid-air. Therefore, early warning of high-amplitude oscillations under random fluctuations has been a major problem faced during the safe flight of the aircraft. Many studies, in recent years, have been devoted to exploring early warning indicators to predict and characterize the onset of high-amplitude oscillations. However, these existing indicators can only warn of high-amplitude oscillations that are impending, which leaves operators not having enough time to avoid the occurrence of these catastrophic events. To overcome these problems, in this paper, we introduce a new and non-local concept: the high-risk region. It can provide early warning signals for the airfoil structure by quantifying the ranges of the system parameters where noise-induced high-amplitude oscillations may occur in advance.

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Sprache(n): eng - Englisch
 Datum: 2022-03-172022-03
 Publikationsstatus: Final veröffentlicht
 Seiten: 13
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1063/5.0084796
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Weather
Model / method: Nonlinear Data Analysis
Working Group: Network- and machine-learning-based prediction of extreme events
 Art des Abschluß: -

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Titel: Chaos
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 32 (3) Artikelnummer: 033119 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: IOP Publishing