Towards reliable turbulence estimations with phase-detection probes: an adaptive window cross-correlation technique
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Air–water flow turbulence was derived from pseudo-instantaneous velocities measured with a dual-tip phase-detection probe. This new technique is proposed based upon adaptive time windows for cross-correlation analysis combined with robust filtering criteria, allowing computation of velocity time series in highly aerated flows. Each velocity estimation corresponded to a small group of bubbles or droplets. Stochastic synthetic velocity fields were generated to assess the limitations and uncertainties related to the proposed analysis. Subsequently, capabilities of the technique were demonstrated through an application to a real two-phase flow on a large-size stepped spillway.
The authors thank Jason Van Der Gevel and Stewart Matthews (The University of Queensland) for the technical assistance and Dr. Antonio Amador for sharing his turbulence dataset. The fruitful discussions with Uriah Gravois are acknowledged. Matthias Kramer was supported by DFG Grant no. KR 4872/2-1.
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