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  Universality in the emergence of oscillatory instabilities in turbulent flows

Pavithran, I., Unni, V. R., Varghese, A. J., Sujith, R. I., Saha, A., Marwan, N., Kurths, J. (2020): Universality in the emergence of oscillatory instabilities in turbulent flows. - EPL (Europhysics Letters), 129, 2, 24004.
https://doi.org/10.1209/0295-5075/129/24004

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 ???ViewItemFull_lblCreators???:
Pavithran, I.1, ???ENUM_CREATORROLE_AUTHOR???
Unni, V. R.1, ???ENUM_CREATORROLE_AUTHOR???
Varghese, A. J.1, ???ENUM_CREATORROLE_AUTHOR???
Sujith, R. I.1, ???ENUM_CREATORROLE_AUTHOR???
Saha, A.1, ???ENUM_CREATORROLE_AUTHOR???
Marwan, Norbert2, ???ENUM_CREATORROLE_AUTHOR???                 
Kurths, Jürgen2, ???ENUM_CREATORROLE_AUTHOR???           
???ViewItemFull_lblAffiliations???:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 ???ViewItemFull_lblAbstract???: Self-organization driven by feedback between subsystems is ubiquitous in turbulent fluid mechanical systems. This self-organization manifests as emergence of oscillatory instabilities and is often studied in different system-specific frameworks. We uncover the existence of a universal scaling behaviour during self-organization in turbulent flows leading to oscillatory instability. Our experiments show that the spectral amplitude of the dominant mode of oscillations scales with the Hurst exponent of a fluctuating state variable following an inverse power law relation. Interestingly, we observe the same power law behaviour with a constant exponent near –2 across various turbulent systems such as aeroacoustic, thermoacoustic and aeroelastic systems.

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???ViewItemFull_lblLanguages???: eng - English
 ???ViewItemFull_lblDates???: 20202020
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.1209/0295-5075/129/24004
???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_EDOC???: 8986
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???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Nonlinear Dynamics
???ENUM_IDENTIFIERTYPE_MODELMETHOD???: Nonlinear Data Analysis
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_WORKINGGROUP???: Development of advanced time series analysis techniques
???ENUM_IDENTIFIERTYPE_WORKINGGROUP???: Network- and machine-learning-based prediction of extreme events
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???ViewItemFull_lblSourceTitle???: EPL (Europhysics Letters)
???ViewItemFull_lblSourceGenre???: ???ENUM_GENRE_JOURNAL???, SCI, Scopus, p3
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???ViewItemFull_lblPages???: ???lbl_noEntry??? ???ViewItemFull_lblSourceVolumeIssue???: 129 (2) ???ViewItemFull_lblSourceSequenceNo???: 24004 ???ViewItemFull_lblSourceStartEndPage???: ???lbl_noEntry??? ???ViewItemFull_lblSourceIdentifier???: ???ENUM_IDENTIFIERTYPE_CONE???: https://publications.pik-potsdam.de/cone/journals/resource/journals132
???ENUM_IDENTIFIERTYPE_PUBLISHER???: IOP Publishing