# The multi-scale nature of Wall shear stress fluctuations in turbulent Rayleigh-Benard convection

## TL;DR

This study investigates long-term wall shear stress fluctuations in turbulent Rayleigh-Benard convection, revealing persistent bi-stable structures, skewed and Gaussian fluctuation distributions, and rare flow reversal events.

## Contribution

It provides the first long-duration measurements of wall shear stress in turbulent RB convection, uncovering bi-stable structures and detailed fluctuation statistics.

## Key findings

- Persistence of bi-stable wall shear stress orientation.
- Skewed Weibull distribution of streamwise shear fluctuations.
- Rare flow reversals linked to rapid shear vector twists.

## Abstract

Measurements of wall shear-stress fluctuations on very long timescales ($\ge$ 1900 free-fall time units) are reported for turbulent Rayleigh-Benard (RB) convection in air at the heated bottom plate of a RB cell, 2.5 m in diameter and 2.5 m in height. The novel sensor simultaneously captures the fluctuations of the magnitude and the direction of the wall shear stress vector $\boldsymbol{\tau}(t)$ with high resolution in the slow air currents. The results show the persistence of a tumble-type structure, which is in a bi-stable state as it oscillates regularly about a mean orientation at a timescale that compares with the typical eddy turnover time. The mean orientation can persist almost hundreds of eddy turnovers, until a re-orientation of this structure in form of a slow precession sets in, while a critical weakening of the mean wall shear stress magnitude - respectively the mean wind - is observed. The amplitudes of turbulent fluctuations in the streamwise wall shear-stress $\tau_x$ along mean wind direction reveal a highly skewed Weibull distribution, while the fluctuations happening on larger time scales follow a symmetric Gaussian distribution. Extreme events such as local flow reversals with negative $\tau_x$ are recovered as rare events and correlate with a rapid angular twist of the wall shear-stress vector. Those events - linked to critical points in the skin friction field - correlate with the coincidence of signals at the tails in both probability distributions.