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  Mitigation of oscillatory instability in turbulent reactive flows: A novel approach using complex networks

Krishnan, A., Manikandan, R., Midhun, P. R., Reeja, K. V., Unni, V. R., Sujith, R. I., Marwan, N., Kurths, J. (2019): Mitigation of oscillatory instability in turbulent reactive flows: A novel approach using complex networks. - EPL (Europhysics Letters), 128, 1, 14003.
https://doi.org/10.1209/0295-5075/128/14003

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Krishnan, A.1, Autor
Manikandan, R.1, Autor
Midhun, P. R.1, Autor
Reeja, K. V.1, Autor
Unni, V. R.1, Autor
Sujith, R. I.1, Autor
Marwan, Norbert2, Autor              
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: We present a novel and an efficient way to mitigate oscillatory instability in turbulent reactive flows. First, we construct weighted spatial correlation networks from the velocity field obtained from high-speed particle image velocimetry. Using network measures, we identify the optimal location for implementing passive control strategies. By injecting micro-jets at this optimal location, we are able to reduce the amplitude of the pressure oscillations to a value comparable to what is observed during the state of stable operation. This approach opens up new avenues to control oscillatory instabilities in turbulent flows.

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 Datum: 2019
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1209/0295-5075/128/14003
PIKDOMAIN: RD4 - Complexity Science
eDoc: 8785
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Tipping Elements
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
 Art des Abschluß: -

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Titel: EPL (Europhysics Letters)
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 128 (1) Artikelnummer: 14003 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals132