Towards reliable turbulence estimations with phase-detection probes: an adaptive window cross-correlation technique

Kramer, Matthias; Valero, Daniel; Chanson, Hubert; Bung, Daniel B.

doi:10.1007/s00348-018-2650-9

Cited by 36 publications

(39 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Special care must be taken in regions with near null velocities and important cross velocities, which lead to oblique impact of bubbles with the probes' tips or bubbles undetected by at least one tip (impacting the cross-correlation performance). The first direct turbulence estimation with phase detection probes in highly aerated flows has been recently presented by Kramer et al [98] through an adaptive cross-correlation approach coupled with robust filtering techniques. However, these findings are yet limited to a stepped spillway model.…”

Section: Discussion On Experimental Uncertaintiesmentioning

confidence: 99%

Numerical Simulation of Hydraulic Jumps. Part 1: Experimental Data for Modelling Performance Assessment

Valero

Viti

Gualtieri

2018

Water

Self Cite

View full text Add to dashboard Cite

Hydraulic jumps have been the object of extensive experimental investigation, providing the numerical community with a complete case study for models’ performance assessment. This study constitutes an exhaustive literature review on hydraulic jumps’ experimental datasets. Both mean and turbulent parameters characterising hydraulic jumps are comprehensively discussed, presenting at least a reference to one dataset. Three studies stand out over other datasets due to their completeness. Using them as reference for model validation may ensure homogeneous and comparable performance assessment for the upcoming numerical models. Experimental inaccuracies are also addressed, allowing the numerical modeller to understand the uncertainties of reduced physical models and its limitations. Part 2 presents the three-dimensional numerical investigations to date and their main achievements.

show abstract

Section: Discussion On Experimental Uncertaintiesmentioning

confidence: 99%

Numerical Simulation of Hydraulic Jumps. Part 1: Experimental Data for Modelling Performance Assessment

Valero

Viti

Gualtieri

2018

Water

Self Cite

View full text Add to dashboard Cite

show abstract

“…Similar to time series obtained with laser Doppler anemometers (LDA), phase-detection probe velocity measurements U (t) may overestimate the mean velocity because more particles pass the measurement volume/hit the probe tips at higher velocities (Britz and Antonia, 1996;Kramer et al, 2019). This shift of the mean velocity towards a higher value is known as velocity bias (McLaughlin and Tiederman, 1973).…”

Section: Time Series Analysismentioning

confidence: 95%

“…Recently, Kramer et al (2019) developed an adaptive window crosscorrelation (AWCC) technique for processing dual-tip phase-detection probe signals. The AWCC Matlab source code is available on GitHub (Kramer and Valero, 2019a).…”

Section: Adaptive Window Cross-correlation (Awcc) Techniquementioning

confidence: 99%

“…To limit erroneous velocity estimations, a robust filtering approach was proposed by Kramer et al (2019), comprising thresholds for 1) the maximum cross-correlation coefficient R 12,i,max , representing the similarity between S 1,i and S 2,i and 2) the secondary peak ratio SPR i = R 12,i,2nd,max /R 12,i,max . SPR i is defined as the ratio of the second tallest peak to the first tallest peak of the cross-correlation function ( figure 1d ) and indicates the presence of one or more events within one windowNote that both parameters detect different physical processes with the aim to characterise the quality of a cross-correlation function.…”

Section: Velocity Estimation and Filteringmentioning

confidence: 99%

“…As residence times are not available for air-water flow data, the synthetic signals of Kramer et al (2019) were re-analysed and three different weighting schemes for the AWCC technique were tested. In Kramer et al (2019), a virtual dual-tip phase-detection probe was immersed in a pattern of randomly distributed fluid particles (following a gamma distribution with 3 mm mean diameter), simulating 1D turbulent motion. The tip separation was ∆x = 4 mm and the probe was sampled for T = 10 s at f = 20 kHz, generating instantaneous void fraction signals.…”

Section: Time Series Analysismentioning

confidence: 99%

See 2 more Smart Citations

Best practices for velocity estimations in highly aerated flows with dual-tip phase-detection probes

Kramer

Hohermuth

Valero

et al. 2020

International Journal of Multiphase Flow

View full text Add to dashboard Cite

Dual-tip phase-detection probes can be used to measure flow properties in gas-liquid flows. Traditionally, time-averaged interfacial velocities have been obtained through cross-correlation analysis of long time-series of phase fraction signals. Using small groups of detected particles, a recently developed adaptive window cross-correlation (AWCC) technique enables the computation of pseudo-instantaneous interfacial velocities and turbulence quantities in highly aerated flows, albeit subject to some smoothing which is due to the use of a finite window duration. This manuscript provides guidance on the selection of optimum processing parameters for the AWCC technique, additionally addressing shortcomings such as velocity bias correction in turbulent flows and extrapolation of turbulence levels to single particles. The presented technique was tested for three highly turbulent air-water flows: smooth and rough-wall boundary layers (tunnel chute and stepped spillway), as well as breaking shear layer flows of a hydraulic jump. Robust estimations of mean velocities and velocity fluctuations were obtained for all flow situations, either using dual-tip conductivity or fiber optical probe data. The computation of integral time scales and velocity spectra is currently limited by the data rate and must be treated with caution.

show abstract

Remote sensing of aerated flows at large dams: proof of concept

Kramer

Felder

2021

Preprint

View full text Add to dashboard Cite

show abstract

Towards reliable turbulence estimations with phase-detection probes: an adaptive window cross-correlation technique

Cited by 36 publications

References 16 publications

Numerical Simulation of Hydraulic Jumps. Part 1: Experimental Data for Modelling Performance Assessment

Numerical Simulation of Hydraulic Jumps. Part 1: Experimental Data for Modelling Performance Assessment

Best practices for velocity estimations in highly aerated flows with dual-tip phase-detection probes

Remote sensing of aerated flows at large dams: proof of concept

Contact Info

Product

Resources

About