A low-dimensional model predicting geometry-dependent dynamics of large-scale coherent structures in turbulence

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 2008). We test the model using Rayleigh-B\'enard convection experiments in a cubic container. The model predicts a new mode in which the alignment of a convection roll switches between diagonals. We observe this mode with a measured switching rate within 30% of the prediction.