Ability of a low-dimensional model to predict geometry-dependent dynamics of large-scale coherent structures in turbulence

Kunlun Bai, Dandan Ji, and Eric Brown
Phys. Rev. E 93, 023117 – Published 26 February 2016

Abstract

We test the ability of a general low-dimensional model for turbulence to predict geometry-dependent dynamics of large-scale coherent structures, such as convection rolls. The model consists of stochastic ordinary differential equations, which are derived as a function of boundary geometry from the Navier-Stokes equations [Brown and Ahlers, Phys. Fluids 20, 075101 (2008); Phys. Fluids 20, 105105 (2008)]. We test the model using Rayleigh-Bénard convection experiments in a cubic container. The model predicts a mode in which the alignment of a convection roll stochastically crosses a potential barrier to switch between diagonals. We observe this mode with a measured switching rate within 30% of the prediction.

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  • Received 19 September 2015

DOI:https://doi.org/10.1103/PhysRevE.93.023117

©2016 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
Fluid Dynamics

Authors & Affiliations

Kunlun Bai, Dandan Ji, and Eric Brown*

  • Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06511, USA

  • *Corresponding author: eric.brown@yale.edu

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Issue

Vol. 93, Iss. 2 — February 2016

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