Abstract
Flow turbulence properties are of utmost importance for the optimization of mixing in stirred vessels. A new experimental-theoretical framework is developed to study such turbulence properties. A discrete wavelet transform is used to decompose Lagrangian flow trajectories measured by positron emission particle tracking into their mean and stochastic components representing different scales. The mean component represents low frequency scale motion or non-diffusive/background motion, while the stochastic component accounts for high frequency scale motion or diffusive motion of small eddies. Decomposed Lagrangian trajectories are used to construct maps of local mean and fluctuation flow velocity, turbulent kinetic energy and its dissipation rate, and, for the first time, turbulent diffusion coefficients. Particle image velocimetry measurements are utilised to independently validate results and tune the input parameters of the analysis. Such detailed information on local mixing scales is invaluable to aid equipment design and operation and facilitate heat/mass transfer and enhance reaction kinetics.
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