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

2019/01/19 by Christoph Bruecker, Bruecker, Christoph, Ronald du Puits +1
Earth and Planetary Sciences · Engineering · Environmental Science · #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Meteorological Phenomena and Simulations #Plant Water Relations and Carbon Dynamics #Wind and Air Flow Studies

paper · pdf · doi:10.48550/arxiv.1901.06577

openalex publication_date 2019/01/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Measurements of wall shear-stress fluctuations on very long timescales (\≥\n1900 free-fall time units) are reported for turbulent Rayleigh-Benard (RB)\nconvection in air at the heated bottom plate of a RB cell, 2.5 m in diameter\nand 2.5 m in height. The novel sensor simultaneously captures the fluctuations\nof the magnitude and the direction of the wall shear stress vector\n boldsymbol\τ(t) with high resolution in the slow air currents. The\nresults show the persistence of a tumble-type structure, which is in a\nbi-stable state as it oscillates regularly about a mean orientation at a\ntimescale that compares with the typical eddy turnover time. The mean\norientation can persist almost hundreds of eddy turnovers, until a\nre-orientation of this structure in form of a slow precession sets in, while a\ncritical weakening of the mean wall shear stress magnitude - respectively the\nmean wind - is observed. The amplitudes of turbulent fluctuations in the\nstreamwise wall shear-stress \τx along mean wind direction reveal a highly\nskewed Weibull distribution, while the fluctuations happening on larger time\nscales follow a symmetric Gaussian distribution. Extreme events such as local\nflow reversals with negative \τx are recovered as rare events and\ncorrelate with a rapid angular twist of the wall shear-stress vector. Those\nevents - linked to critical points in the skin friction field - correlate with\nthe coincidence of signals at the tails in both probability distributions.\n

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