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Probing turbulence intermittency via autoregressive moving-average models

Davide Faranda 1, * Bérengère Dubrulle 1 François Daviaud 1 Flavio Maria 2 Emanuele Pons 2 
* Corresponding author
1 SPHYNX - Systèmes Physiques Hors-équilibre, hYdrodynamique, éNergie et compleXes
SPEC - UMR3680 - Service de physique de l'état condensé, IRAMIS - Institut Rayonnement Matière de Saclay
Abstract : We suggest an approach to probing intermittency corrections to the Kolmogorov law in turbulent flows based on the autoregressive moving-average modeling of turbulent time series. We introduce an index ϒ that measures the distance from a Kolmogorov-Obukhov model in the autoregressive moving-average model space. Applying our analysis to particle image velocimetry and laser Doppler velocimetry measurements in a von Kármán swirling flow, we show that ϒ is proportional to traditional intermittency corrections computed from structure functions. Therefore, it provides the same information, using much shorter time series. We conclude that ϒ is a suitable index to reconstruct intermittency in experimental turbulent fields.
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Davide Faranda, Bérengère Dubrulle, François Daviaud, Flavio Maria, Emanuele Pons. Probing turbulence intermittency via autoregressive moving-average models. Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, American Physical Society, 2014, 90, pp.061001(R). ⟨10.1103/PhysRevE.90.061001⟩. ⟨cea-01370472⟩



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