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Fluid particle accelerations in fully developed turbulence

Author

Listed:
  • A. La Porta

    (Laboratory of Atomic and Solid State Physics, Laboratory of Nuclear Studies, Cornell University, Ithaca)

  • Greg A. Voth

    (Laboratory of Atomic and Solid State Physics, Laboratory of Nuclear Studies, Cornell University, Ithaca)

  • Alice M. Crawford

    (Laboratory of Atomic and Solid State Physics, Laboratory of Nuclear Studies, Cornell University, Ithaca)

  • Jim Alexander

    (Laboratory of Atomic and Solid State Physics, Laboratory of Nuclear Studies, Cornell University, Ithaca)

  • Eberhard Bodenschatz

    (Laboratory of Atomic and Solid State Physics, Laboratory of Nuclear Studies, Cornell University, Ithaca)

Abstract

The motion of fluid particles as they are pushed along erratic trajectories by fluctuating pressure gradients is fundamental to transport and mixing in turbulence. It is essential in cloud formation and atmospheric transport1,2, processes in stirred chemical reactors and combustion systems3, and in the industrial production of nanoparticles4. The concept of particle trajectories has been used successfully to describe mixing and transport in turbulence3,5, but issues of fundamental importance remain unresolved. One such issue is the Heisenberg–Yaglom prediction of fluid particle accelerations6,7, based on the 1941 scaling theory of Kolmogorov8,9. Here we report acceleration measurements using a detector adapted from high-energy physics to track particles in a laboratory water flow at Reynolds numbers up to 63,000. We find that, within experimental errors, Kolmogorov scaling of the acceleration variance is attained at high Reynolds numbers. Our data indicate that the acceleration is an extremely intermittent variable—particles are observed with accelerations of up to 1,500 times the acceleration of gravity (equivalent to 40 times the root mean square acceleration). We find that the acceleration data reflect the anisotropy of the large-scale flow at all Reynolds numbers studied.

Suggested Citation

  • A. La Porta & Greg A. Voth & Alice M. Crawford & Jim Alexander & Eberhard Bodenschatz, 2001. "Fluid particle accelerations in fully developed turbulence," Nature, Nature, vol. 409(6823), pages 1017-1019, February.
    • Handle: RePEc:nat:nature:v:409:y:2001:i:6823:d:10.1038_35059027
    DOI: 10.1038/35059027
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    Cited by:

    1. Huang, Diangui, 2019. "A new turbulence analysis method based on the mean speed and mean free path theory of the molecule thermal motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 66-74.
    2. Sun, HongGuang & Hao, Xiaoxiao & Zhang, Yong & Baleanu, Dumitru, 2017. "Relaxation and diffusion models with non-singular kernels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 590-596.
    3. Carvalho, Jonas C. & Rizza, Umberto & Lovato, Rodrigo & Degrazia, Gervásio A. & Filho, Edson P.M. & Campos, Cláudia R.J., 2009. "Estimation of the Kolmogorov constant by large-eddy simulation in the stable PBL," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1500-1508.
    4. Na, Ji Sung & Koo, Eunmo & Ko, Seung Chul & Linn, Rodman & Muñoz-Esparza, Domingo & Jin, Emilia Kyung & Lee, Joon Sang, 2019. "Stochastic characteristics for the vortical structure of a 5-MW wind turbine wake," Renewable Energy, Elsevier, vol. 133(C), pages 1220-1230.
    5. Simone Ferrari & Riccardo Rossi & Annalisa Di Bernardino, 2022. "A Review of Laboratory and Numerical Techniques to Simulate Turbulent Flows," Energies, MDPI, vol. 15(20), pages 1-56, October.
    6. Chen, W., 2006. "Time–space fabric underlying anomalous diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 28(4), pages 923-929.

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