Probabilistic High-Density Particle-Tracking-Velocimetry Of Turbulent Flow Structures In A Cubic Rayleigh-Bénard Convection Cell
R. Barta (1,2), D. Schiepel (1), S. Herzog (3), C. Wagner (1,2)
(1) Institute of Aerodynamics and Flow Technology, German Aerospace Center (DLR), Germany
(2) Institute of Thermodynamics and Fluid Mechanics, Technische Universität Ilmenau, Germany
(3) Department for Computational Neuroscience, University of Göttingen, Germany
DOI:
We apply a new probabilistic python-based high-density Particle-Tracking-Velocimetry (pyHDPTV) method and the commercial Shake-The-Box (STB) algorithm from LaVision (DaVis v10.2.0) to measured data of a turbulent Rayleigh-Bénard (RB) convection in a cubic cell. The measurement was performed in water (Prandtl number Pr ≈ 7) with a seeding particle densities of ρ ≈ 0:04 ppp at the hard turbulence regime with Rayleigh number Ra ≈ 1E10.
