Large-scale flow in a cubic Rayleigh-B\'{e}nard cell: Long-term turbulence statistics and Markovianity of macrostate transitions

TL;DR

This study uses long-term and ensemble numerical simulations to analyze large-scale circulation dynamics in turbulent Rayleigh-Bénard convection within a cubic cell, revealing Markovian transition behavior among flow states.

Contribution

It provides the first detailed analysis of macrostate transitions and Markovianity in large-scale turbulent convection in a cubic cell at high Rayleigh number.

Findings

Large-scale flow depends strongly on Prandtl number.

Transition probabilities suggest Markovian dynamics.

Flow exhibits four macrostate states with Markovian transitions.

Abstract

We investigate the large-scale circulation (LSC) in a turbulent Rayleigh-B\'enard convection flow in a cubic closed convection cell by means of direct numerical simulations at a Rayleigh number $Ra=10^6$. The numerical studies are conducted for single flow trajectories up to $10^5$ convective free-fall times to obtain a sufficient sampling of the four discrete LSC states, which can be summarized to one macrostate, and the two crossover configurations which are taken by the flow in between for short periods. We find that large-scale dynamics depends strongly on the Prandtl number $Pr$ of the fluid which has values of 0.1, 0.7, and 10. Alternatively, we run an ensemble of 3600 short-term direct numerical simulations to study the transition probabilities between the discrete LSC states. This second approach is also used to probe the Markov property of the dynamics. Our ensemble analysis gave strong indication of Markovianity of the transition process from one LSC state to another, even though the data are still accompanied by considerable noise. It is based on the eigenvalue spectrum of the transition probability matrix, further on the distribution of persistence times and the joint distribution of two successive macrostate persistence times.