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Multi-scale statistics of turbulence motorized by active matter

Published online by Cambridge University Press:  08 June 2017

J. Urzay ,
A. Doostmohammadi Open the ORCID record for A. Doostmohammadi [Opens in a new window]  and
J. M. Yeomans Open the ORCID record for J. M. Yeomans [Opens in a new window]
J. Urzay*
Affiliation:
Center for Turbulence Research, Stanford University, CA 94305-3024, USA
A. Doostmohammadi
Affiliation:
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, OX1 3NP, UK
J. M. Yeomans
Affiliation:
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, OX1 3NP, UK
*
†Email address for correspondence: jurzay@stanford.edu
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Abstract

A number of micro-scale biological flows are characterized by spatio-temporal chaos. These include dense suspensions of swimming bacteria, microtubule bundles driven by motor proteins and dividing and migrating confluent layers of cells. A characteristic common to all of these systems is that they are laden with active matter, which transforms free energy in the fluid into kinetic energy. Because of collective effects, the active matter induces multi-scale flow motions that bear strong visual resemblance to turbulence. In this study, multi-scale statistical tools are employed to analyse direct numerical simulations (DNS) of periodic two-dimensional (2-D) and three-dimensional (3-D) active flows and to compare the results to classic turbulent flows. Statistical descriptions of the flows and their variations with activity levels are provided in physical and spectral spaces. A scale-dependent intermittency analysis is performed using wavelets. The results demonstrate fundamental differences between active and high-Reynolds-number turbulence; for instance, the intermittency is smaller and less energetic in active flows, and the work of the active stress is spectrally exerted near the integral scales and dissipated mostly locally by viscosity, with convection playing a minor role in momentum transport across scales.

JFM classification

Multiphase and Particle-laden Flows: Multiphase and Particle-laden Flows Turbulent Flows: Turbulent Flows
Type
Papers
Information
Journal of Fluid Mechanics , Volume 822 , 10 July 2017 , pp. 762 - 773
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Copyright
© 2017 Cambridge University Press 

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Footnotes

‡

Both authors contributed equally to this work.

References

Bratanov, V., Jenko, F. & Frey, E. 2015 New class of turbulence in active fluids. Proc. Natl Acad. Sci. USA 112, 15048–15053.Google Scholar
De Gennes, P. G. & Prost, J. 1995 The Physics of Liquid Crystals. Oxford University Press.Google Scholar
Doostmohammadi, A., Adamer, M. F., Thampi, S. P. & Yeomans, J. M. 2016b Stabilization of active matter by flow-vortex lattices and defect ordering. Nat. Commun. 7, 10557.Google Scholar
Doostmohammadi, A., Shendruk, T. N., Thijssen, K. & Yeomans, J. M. 2017 Onset of meso-scale turbulence in active nematics. Nat. Commun. 8, 15326.CrossRefGoogle ScholarPubMed
Doostmohammadi, M. F., Thampi, S. P. & Yeomans, J. M. 2016a Defect-mediated morphologies in growing cell colonies. Phys. Rev. Lett. 117, 048102.Google Scholar
Dunkel, J., Heidenreich, S., Drescher, K., Wensink, H. H., Bär, M. & Goldstein, R. E. 2013 Fluid dynamics of bacterial turbulence. Phys. Rev. Lett. 110, 228102.CrossRefGoogle ScholarPubMed
Edwards, B., Beris, A. N. & Grmela, M. 1991 The dynamical behavior of liquid crystals: a continuum description through generalized brackets. Mol. Cryst. Liq. Cryst. 201 (1), 51–86.Google Scholar
Giomi, L. 2015 Geometry and topology of turbulence in active nematics. Phys. Rev. X 5, 031003.Google Scholar
Meneveau, C. 1991 Analysis of turbulence in the orthonormal wavelet representation. J. Fluid Mech. 232, 469–520.Google Scholar
Nguyen, R. V. Y., Farge, M. & Schneider, K. 2012 Scale-wise coherent vorticity extraction for conditional statistical modeling of homogeneous isotropic two-dimensional turbulence. Physica D 241, 186–201.Google Scholar
Ottino, J. M. 1990 Mixing, chaotic advection, and turbulence. Annu. Rev. Fluid Mech. 22, 207–253.CrossRefGoogle Scholar
Sanchez, T., Chen, D. T. N., DeCamp, S. J., Heymann, M. & Dogic, Z. 2012 Spontaneous motion in hierarchically assembled active matter. Nature 491, 431–434.Google Scholar
Saw, T. B., Doostmohammadi, A., Nier, V., Kocgozlu, L., Thampi, S., Toyama, Y., Marcq, P., Lim, C. T., Yeomans, J. M. & Ladoux, B. 2017 Topological defects in epithelia govern cell death and extrusion. Nature 544, 212–216.Google Scholar
Schneider, K. & Vasilyev, O. V. 2010 Wavelet methods in computational fluid dynamics. Annu. Rev. Fluid Mech. 42, 473–503.Google Scholar
Simha, A. & Ramaswamy, S. 2002 Hydrodynamic fluctuations and instabilities in ordered suspensions of self-propelled particles. Phys. Rev. Lett. 89, 058101.Google Scholar
Thampi, S. P., Golestanian, R. & Yeomans, J. M. 2013 Velocity correlations in an active nematic. Phys. Rev. Lett. 111, 118101.Google Scholar
Wensink, H. H., Dunkel, J., Heidenreich, S., Drescher, K., Goldstein, R. E., Lowen, H. & Yeomans, J. M. 2012 Meso-scale turbulence in living fluids. Proc. Natl Acad. Sci. USA 109, 14308–14313.Google Scholar