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.
Faranda, D., Dubrulle, B., Daviaud, F., Pons, F.M.E. (2014). Probing turbulence intermittency via autoregressive moving-average models. PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS, 90(6), 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.