Reynolds-number scaling of wall-pressure--velocity correlations in wall-bounded turbulence

TL;DR

This paper investigates how wall-pressure and velocity correlations scale with Reynolds number in wall-bounded turbulence, using DNS data and experimental validation to inform control strategies based on wall-pressure signals.

Contribution

It provides a detailed analysis of the Reynolds-number dependence of wall-pressure--velocity correlations and demonstrates the potential for wall-pressure data to predict turbulent states for control.

Findings

Peak coupling at specific wall-scaling wavelengths

Stronger coherence with quadratic wall-pressure terms

Achieved 72% accuracy in predicting velocity states from wall-pressure

Abstract

Wall-pressure fluctuations are a practically robust input for real-time control systems aimed at modifying wall-bounded turbulence. The scaling behaviour of the wall-pressure--velocity coupling requires investigation to properly design a controller with such input data so that it can actuate upon the desired turbulent structures. A comprehensive database from direct numerical simulations of turbulent channel flow is used for this purpose, spanning a Reynolds-number range $Re_\tau \approx 550$-$5\,200$. Spectral analysis reveals that the streamwise velocity is most strongly coupled to the linear term of the wall-pressure, at a wall-scaling of $\lambda_x/y \approx 14$ (and $\lambda_x/y \approx 8.5$ for the wall-normal velocity). When extending the analysis to both homogeneous directions in $x$ and $y$, the peak-coherence is centred at $\lambda_x/\lambda_z \approx 2$ and $\lambda_x/\lambda_z \approx 1$ for $p_w$ and $u$, and $p_w$ and $v$, respectively. A stronger coherence is retrieved when the quadratic term of the wall-pressure is concerned, but there is only little evidence for a wall-attached-eddy type of scaling. Experimental data are explored in the second part of this work: wall-pressure data are denoised and subsequently used for predicting the binary-state of the streamwise velocity fluctuations in the logarithmic region. A binary estimation accuracy of up to 72% can be achieved by including both the linear and quadratic terms of the wall-pressure. This study demonstrates that a controller for wall-bounded turbulence (solely relying on wall-pressure data) has merit in terms of a sufficient state estimation capability, even in the presence of significant facility noise.