English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  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

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Pavithran, I.1, Author
Unni, V. R.1, Author
Varghese, A. J.1, Author
Sujith, R. I.1, Author
Saha, A.1, Author
Marwan, Norbert2, Author              
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 Abstract: 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.

Details

show
hide
Language(s): eng - English
 Dates: 20202020
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1209/0295-5075/129/24004
PIKDOMAIN: RD4 - Complexity Science
eDoc: 8986
MDB-ID: No data to archive
Research topic keyword: Nonlinear Dynamics
Model / method: Nonlinear Data Analysis
Organisational keyword: RD4 - Complexity Science
Working Group: Development of advanced time series analysis techniques
Working Group: Network- and machine-learning-based prediction of extreme events
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: EPL (Europhysics Letters)
Source Genre: Journal, SCI, Scopus, p3
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 129 (2) Sequence Number: 24004 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals132
Publisher: IOP Publishing