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Vortex dynamics and Lagrangian statistics in a model for active turbulence.

Martin James1, Michael Wilczek2

  • 1Max Planck Institute for Dynamics and Self-Organization (MPI DS), Am Faßberg 17, 37077, Göttingen, Germany.

The European Physical Journal. E, Soft Matter
|February 14, 2018
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Summary

Dense bacterial flows can exhibit active turbulence. This study statistically analyzes active turbulence using numerical methods, exploring velocity statistics and vortex dynamics to understand its Gaussian-like large-scale behavior.

Keywords:
Topical issue: Fluids and Structures: Multi-scale coupling and modeling

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Area of Science:

  • Physics
  • Fluid Dynamics
  • Biophysics

Background:

  • Cellular suspensions, like dense bacterial flows, can exhibit complex emergent behaviors.
  • Under specific conditions, these systems display a
  • active turbulence
  • phenomenon, characterized by chaotic, swirling motion.
  • Understanding active turbulence is crucial for fields ranging from microbiology to materials science.

Purpose of the Study:

  • To statistically investigate the phenomenon of active turbulence in dense bacterial flows.
  • To characterize the scale-dependent features of two-point velocity statistics in Eulerian and Lagrangian frames.
  • To analyze vortex dynamics within active turbulence.

Main Methods:

  • Numerical modeling using a generalized Navier-Stokes equation, following Wensink et al.
  • Statistical analysis of two-point velocity correlations in both Eulerian and Lagrangian reference frames.
  • Quantitative measurements of vortex dynamics.

Main Results:

  • The study provides statistical characterization of active turbulence.
  • Scale-dependent features of two-point velocity statistics were identified.
  • Vortex dynamics were measured and analyzed in conjunction with statistical properties.
  • Large-scale statistics of active turbulence were found to be close to Gaussian, exhibiting sub-Gaussian tails.

Conclusions:

  • Active turbulence in cellular suspensions shares statistical similarities with classical turbulence.
  • The generalized Navier-Stokes equation provides a valid framework for modeling active turbulence.
  • The observed statistical properties offer insights into the collective behavior of self-propelled particles.