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.
Probing turbulence intermittency via autoregressive moving-average models / Faranda, Davide; Dubrulle, Bérengère; Daviaud, François; Pons, Flavio Maria Emanuele. - In: PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS. - ISSN 1539-3755. - ELETTRONICO. - 90:6(2014), pp. 061001.061001-061001.061004. [10.1103/PhysRevE.90.061001]
Probing turbulence intermittency via autoregressive moving-average models
Pons, Flavio Maria Emanuele
2014
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.