Convection of multi-scale motions in turbulent boundary layer by temporal resolution particle image velocimetry

Abstract

Experiments of particle image velocimetry (PIV) in the turbulent boundary layer at $R{e}_{\tau }=400\sim 1000$ have been conducted to investigate the convection characteristic of turbulent structure and the validity of Taylor’s hypothesis. Views of $6\delta \times 1.2\delta$ ($\delta ={\delta }_{99}$, the boundary layer thickness) were captured by four streamwise-arranged cameras. Distributions of streamwise turbulent kinetic energy on a streamwise scale were investigated by continuous-wave transform, and scales were found where the portion of streamwise turbulent kinetic energy approaches maximum. Fluctuating velocities (instant velocity minus average velocity on time dimension) were divided into large-scale motion (LSM) and small-scale motion (SSM) portions, bounded by $1\delta$. Convection velocities of LSM and SSM are determined by the spatiotemporal correlation method, and they are larger than local average velocities in near-wall regions, but smaller than local average velocities in wake regions. Statistical characteristics between velocity fields reconstructed by Taylor’s hypothesis and original fields were compared by the autocorrelation method, and the reconstructed field’s patterns are longer than original field’s patterns, while their heights do not have clear distinction. The correlation of original velocity fields and reconstructed fields shows that LSM can hold on over $3\delta$ and SSM over $1\delta$ in streamwise convection separation for regions of $y/\delta >0.2$, given a threshold value (correlation coefficient C = 0.6).

KEYWORDS:

• Turbulent boundary layers
• convection velocity
• wavelet
• PIV
• Taylor hypothesis

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Chinesisch-Deutsche Zentrum für Wissenschaftsförderung [grant number GZ1575]; Ministry of Industry and Information Technology of China [grant number [2019]360]; National Natural Science Foundation of China [grant number 11732010,11872272,11902218,11972251]; Open Project Program of the Key Laboratory of Aerodynamic Noise Control [grant number ANCL20200105]; Peiyang Young Scholars Program of Tianjin University [grant number 2020XRG-0033].