Statistical and Temporal Characterization of Turbulent Rayleigh-Bénard Convection Boundary Layers Using Time-Resolved PIV Measurements

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This contribution reports on near-wall flow field measurements in turbulent Rayleigh-Benard convection (RBC) in air at a fixed Prandtl number \(\mathrm {Pr} = 0.7\) and Rayleigh number \(\mathrm {Ra} = 1.45 \times 10^{10}\). For the experiment, the large-scale convection (LSC) was confined to a rectangular box of \(2.5 \times 2.5 \times 0.65\,\mathrm {m}^3\) made of transparent acrylic sheets. Prior video-graphic visualizations of the bottom boundary layer flow by means of laser light sheet illumination of small particles indicated the presence of highly dynamic flow behaviour at flow conditions that classical stability analysis predicts to still be in the laminar regime. While theory predicts a transition to turbulence at Reynolds numbers \(\mathrm {Re}_\delta \approx 420\), the present investigation exhibits highly unsteady flow at a much lower Reynolds number of \(\mathrm {Re}_\delta \approx 260\) based on boundary layer thickness. With the help of the PIV data, it can be demonstrated that the entrainment of turbulent structures from the mean wind into the boundary layer acts, alongside with the destabilization due to inner shear, as a second mechanism on its path to turbulence. Both contributions must be considered when predicting the critical bound towards the ultimate regime of thermal convection. The measurements rely on the acquisition of long, continuous sequences of particle image velocimetry (PIV) data from which both statistical and spectral information can be retrieved. Contrary to conventional implementation of the PIV technique the field of view is restricted to a narrow strip, generally extending in wall-normal direction. In this way, both the acquisition frequency and the total number images of the employed high-speed camera are proportionally increased. The temporally oversampled data allows the use of multi-frame PIV processing algorithms which reduce measurement uncertainties with respect to standard dual-frame analysis.