Reynolds decomposition of turbulence containing super-coherent states

Ronald Adrian, P. J. Sakievich, Yulia Peet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A vexing problem occurs in certain flows when long, but finite, time-average estimates of the mean flow fail to exhibit the symmetry properties imposed by boundary conditions and physics. The mean field becomes suspect, making it difficult, or even incorrect to apply Reynolds decomposition. The problem occurs when the flow exhibits "super-coherent" states, i.e. states of flow having coherence times much longer than the averaging times used in typical turbulence experiments. Turbulent Rayleigh-Benard convection (RBC) is one such flow, and it will be used here as an example to illustrate and explain this phenomenon. The study focuses on a turbulent RBC experiment (Fernandes, 2001) in a 6.3:1 (diameter: depth) aspect-ratio vertical cylinder that supplemented time averaging with true ensemble averaging to achieve almost zero mean flow. To obtain a three-dimensional time-varying picture of the mechanisms at work, the experiment is simulated by direct numerical simulation of the Boussinesq equations (Sakievich et al., 2016). Three types of super-coherent states, associated with the symmetries of the flow, are found to bias the mean flow, unless steps are taken to sample each state with equal probability. They are azimuthal composition and orientation of the large-scale structures, the direction of azimuthal drift, and the preferential direction of the large-scale central motions.

Original languageEnglish (US)
Title of host publication10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017
PublisherInternational Symposium on Turbulence and Shear Flow Phenomena, TSFP10
Volume1
ISBN (Electronic)9780000000002
StatePublished - 2017
Event10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017 - Chicago, United States
Duration: Jul 6 2017Jul 9 2017

Other

Other10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017
CountryUnited States
CityChicago
Period7/6/177/9/17

Fingerprint

Turbulence
turbulence
decomposition
Decomposition
Experiments
Direct numerical simulation
Aspect ratio
Physics
Boundary conditions
symmetry
convection
Chemical analysis
Boussinesq equation
experiment
boundary condition
physics
Convection
simulation

ASJC Scopus subject areas

  • Atmospheric Science
  • Aerospace Engineering

Cite this

Adrian, R., Sakievich, P. J., & Peet, Y. (2017). Reynolds decomposition of turbulence containing super-coherent states. In 10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017 (Vol. 1). International Symposium on Turbulence and Shear Flow Phenomena, TSFP10.

Reynolds decomposition of turbulence containing super-coherent states. / Adrian, Ronald; Sakievich, P. J.; Peet, Yulia.

10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017. Vol. 1 International Symposium on Turbulence and Shear Flow Phenomena, TSFP10, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Adrian, R, Sakievich, PJ & Peet, Y 2017, Reynolds decomposition of turbulence containing super-coherent states. in 10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017. vol. 1, International Symposium on Turbulence and Shear Flow Phenomena, TSFP10, 10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017, Chicago, United States, 7/6/17.
Adrian R, Sakievich PJ, Peet Y. Reynolds decomposition of turbulence containing super-coherent states. In 10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017. Vol. 1. International Symposium on Turbulence and Shear Flow Phenomena, TSFP10. 2017
Adrian, Ronald ; Sakievich, P. J. ; Peet, Yulia. / Reynolds decomposition of turbulence containing super-coherent states. 10th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2017. Vol. 1 International Symposium on Turbulence and Shear Flow Phenomena, TSFP10, 2017.
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