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Area of Science:

  • Fluid Dynamics
  • Turbulence Research
  • Statistical Physics

Background:

  • The Kolmogorov law describes energy dissipation in turbulent flows.
  • Intermittency corrections are necessary to accurately model turbulent phenomena.
  • Traditional methods for analyzing intermittency require extensive time series data.

Purpose of the Study:

  • To develop a novel approach for probing intermittency corrections in turbulent flows.
  • To introduce a new index (Υ) for quantifying deviations from the Kolmogorov-Obukhov model.
  • To assess the efficiency of the proposed method compared to existing techniques.

Main Methods:

  • Autoregressive moving-average (ARMA) modeling of turbulent time series.
  • Introduction and application of the index Υ.
  • Analysis of particle image velocimetry (PIV) and laser Doppler velocimetry (LDV) data from a von Kármán swirling flow.

Main Results:

  • The index Υ effectively measures the distance from the Kolmogorov-Obukhov model in the ARMA model space.
  • Υ is shown to be proportional to traditional intermittency corrections derived from structure functions.
  • The proposed method yields the same information as traditional methods but requires significantly shorter time series.

Conclusions:

  • The developed ARMA-based approach provides an efficient way to study intermittency in turbulent flows.
  • The index Υ is a suitable metric for reconstructing intermittency in experimental turbulent fields.
  • This method offers a more data-efficient alternative for analyzing turbulent phenomena.