Evaluating phase-detection-based approaches for interfacial velocity and turbulence intensity estimation in a highly-aerated hydraulic jump. (October 2021)

• Record Type: Journal Article
• Authors: Wang, Kun; Tang, Rongcai; Bai, Ruidi; Wang, Hang
• Is Part Of: Flow measurement and instrumentation. Volume 81(2021)
• Publication Date: 2021-10
• Subjects: Hydraulic jump -- Phase-detection probe -- Turbulence intensity -- Full-signal cross-correlation -- Adaptive-window cross-correlation -- Manual bubble identification; Fluid dynamic measurements -- Periodicals; Flow meters -- Periodicals; Fluides, Dynamique des -- Mesure -- Périodiques; Débitmètres -- Périodiques; 681.2805
• DOI: 10.1016/j.flowmeasinst.2021.102045
• Languages: English
• ISSNs: 0955-5986

Abstract

Abstract: Estimation of turbulence intensity within a highly-aerated turbulent flow is challenging. A possible way is to record bubble arrival information using intrusive phase-detection probes, but the derivation of velocity variation is subject to the correlation and de-correlation of the signals, especially in highly-turbulent and rapidly-varied flows with complex bubble transport such as in hydraulic jumps. Although attempts have been devoted to the improvement of data processing, it is difficult to assess the existing approaches in strong hydraulic jumps due to the lack of alternative measurement techniques applicable to the internal air-water flow region. In this letter, a substantial amount of work is devoted to manual analysis of instantaneous interfacial velocity in strong hydraulic jumps, and the velocity variation results are compared with the results of full-signal cross-correlation and adaptive-window cross-correlation approaches, to evaluate their performance in approximating the velocity turbulence. The manual results are validated in terms of the time-averaged velocity. The interfacial turbulence intensity is suggested to be greater than the water-phase velocity turbulence, typically between 20% and 40% in the unidirectional jet-shear region. Overall the manual results agree better with the calculation of adaptive-window cross-correlation technique. The relevance of the signal decomposition processing is also discussed, and it is emphasized that the phase-detection-based approaches are subject to the limitations of one-dimensional measurements in a complex three-dimensional flow. Highlights: Introduced manual bubble identification approach for interfacial turbulence estimation. Compared different phase-detection-based turbulence estimators in strong hydraulic jumps. Discussed the capacity and limitation of assessed turbulence estimation approaches.