Application of post-processing methods on the velocity statistics measured at different sampling frequencies using acoustic Doppler velocimeter

Document Type : Research Article


Assistant Professor, Department of Civil and Environmental Engineering, Amirkabir University of Technology (Tehran Polytechnic


Introduction: In analyzing of hydraulic phenomena and turbulent flow problems, the most appropriate solution is to use physical and laboratory models. Due to the effects of precise measurement in the experimental works, in the turbulent flow fields, accurate measurement of velocity components helps to a better understanding of flow dynamics. Acoustic Doppler velocimetry (ADV) is a velocity measurement instrument and is among the most widely used methods in various hydraulic engineering applications both in the laboratory and field. The ADV instrument measures both of the mean and fluctuating characteristics of all three components of the velocity field. The most important reasons for using the ADV as a priority to other velocity measurement techniques are the portability of the device, the ability to measure turbid current, and the three-dimensional velocity measurement. Due to the presence of noise and spikes in ADV's velocity measurements, statistical parameters of velocity may be affected. For this reason, the post-processing of velocity measurements of acoustic Doppler velocimetry is essential in the hydraulic based research. Most of the studies in this field have been carried out within the channel, where the turbulence intensity is relatively low. So, it is necessary to evaluate the efficiency of the proposed methods in the flows, especially with high turbulence intensity.
Methodology: The experiments were carried out at the hydraulic laboratory of the civil engineering department of Amirkabir University. To minimize wall effects, experiments were carried out in a 1 × 1.7 × 0.54 m3 upstream basin connected to a 6-m-long flume filled with water. An axisymmetric turbulent jet with a circular cross-section with 1cm diameter was emitted into the upstream basin with quiescent water. The jet was fed from a constant-head tank. A Georg Fischer d32 (Schaffhausen, Switzerland) DN 25 flowmeter with a measurement accuracy of 1% (of full-scale value) maintained to adjust the jet flow with a Reynolds number of 10000. The temperature of the water in the jet and that of the water in the basin were the same because the jet was fed from the water of the flume. The velocity field was measured using Nortek Vectrino Plus ADV at two sampling frequencies of 25 and 200 Hz in the self-similarity region. The instrument’s probe consisted of four ceramic receivers and one ceramic transmitter connected to the electronics housing by a stem. To validate the ADV measurements, experiments were carried out in the self-similar zone of an axisymmetric turbulent jet issued into quiescent water. Different types of spike removal and noise reduction filters, such as Goring and Nikora (spike removal), Hurther and Lemmin, and Khorsandi et al. (noise reduction), as well as their combination, have been used to improve the velocity statistics measured at different sampling frequencies. Results were compared with the measurements conducted using other techniques in past research such as Panchapakesan and Lumley (1993), Darisse et al. (2015), and Hussein et al. (1994).
Results and discussion: ADV measurement verification shows that the amounts of spreading rate (S) and decay rate (B) of the jet are in a good agreement with previous studies that used different types of velocity measurement tools. Results highlight that changing sampling frequency does not significantly affect the amounts of decay rate and spreading rate. It is observed that the spike effect on the mean axial velocity is negligible. Evaluation of the velocity variance for the different ADV sampling frequencies reveals that noise causes a difference in the velocity measurement by different sampling frequencies. Applying different filters to velocity measurement data shows that Khorsandi et al. filter has the best agreement with the previous study. Results also show that Khorsandi et al. filter less dependent on the sampling frequency changing. In the near field of the jet nozzle, a combination of spike and noise post-processing filters has more efficiency on 200Hz sampling frequency data. This can be attributed to the presence of more spikes and noise in the area with more turbulence intensity. Applying combinations of both noise and spike post-processing filters improves the accuracy of the results.
Conclusion: Results revealed that the velocity variances measured at the higher sampling frequency were overestimated when compared to those measured at the lower sampling frequency. Post-processing of the data resulted in a better agreement of the statistics measured at different sampling frequencies. The application of combinations of both noise and spike filters are more effective than just using one filter. Finally, for the post-processing of velocity field measurements or near boundary flow measurements with low-quality data, the application of both the noise and spike filters is recommended.


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