Investigation of the spatio-temporal flow structure in the log-law region of a turbulent boundary layer by means of multi-plane stereo particle image velocimetry

Kähler, Christian J.; Stanislas, Michel; Dewhirst, T.; Carlier, Johan

doi:10.1007/978-3-662-08263-8_3

Cited by 11 publications

(5 citation statements)

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“…The stereoscopic PIV measurements were carried out by Kähler et al (2000) and are available in the WALLTURB database. They were recorded with a 2 × 330 mJ BMI ND-YAG laser, with two synchronized PCO cameras (CCD array of 1024 × 1280 pixels) mounted in an angular configuration with Scheimpflug correction.…”

Section: Methodsmentioning

confidence: 99%

“…This correlation can be assessed from streamwise/wall normal (x, y) PIV data. This was performed here from the PIV data recorded by Kähler et al (2000) which are stored in the WALLTURB database (wallturb.univ-lille1.fr). Figure 28 shows the plot of this quantity as a function of y + for the two Reynolds numbers available, together with u 2 /y.…”

Section: Fluctuating Vorticity Budgetmentioning

confidence: 99%

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Vortical structures in the turbulent boundary layer: a possible route to a universal representation

2008

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A study of streamwise oriented vortical structures embedded in turbulent boundary layers is performed by investigating an experimental database acquired by stereoscopic particle image velocimetry (SPIV) in a plane normal both to the mean flow and the wall. The characteristics of the experimental data allow us to focus on the spatial organization within the logarithmic region for Reynolds numbers Reθ up to 15000. On the basis of the now accepted hairpin model, relationships and interaction between streamwise vortices are first investigated via computation of two-point spatial correlations and the use of linear stochastic estimation (LSE). These analyses confirm that the shape of the most probable coherent structures corresponds to an asymmetric one-legged hairpin vortex. Moreover, two regions of different dynamics can be distinguished: the near-wall region below y+=150, densely populated with strongly interacting vortices; and the region above y+=150 where interactions between eddies happen less frequently. Characteristics of the detected eddies, such as probability density functions of their radius and intensity, are then studied. It appears that Reynolds number as well as wall-normal independences of these quantities are achieved when scaling with the local Kolmogorov scales. The most probable size of the detected vortices is found to be about 10 times the Kolmogorov length scale. These results lead us to revisit the equation for the mean square vorticity fluctuations, and to propose a new balance of this equation in the near-wall region. This analysis and the above results allow us to propose a new description of the near-wall region, leading to a new scaling which seems to have a good universality in the Reynolds-number range investigated. The possibility of reaching a universal scaling at high enough Reynolds number, based on the external velocity and the Kolmogorov length scale is suggested.

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Section: Methodsmentioning

confidence: 99%

Section: Fluctuating Vorticity Budgetmentioning

confidence: 99%

Vortical structures in the turbulent boundary layer: a possible route to a universal representation

2008

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“…For comparison, data from Hutchins et al (2009) (hot-wire data, similar Re τ ) and Eitel-Amor et al (2014) (numerical data, similar Reθ) are included. In addition, Stereo-PIV data from Kähler et al (2002) and Tomo-PIV data from Laskari et al (2016) are included for validation. Mean and fluctuations of streamwise velocity are well captured and consistent trends are found for the wall-normal velocity fluctuations and Reynolds shear-stress.…”

Section: Experimental Methodsmentioning

confidence: 99%

Structure of high and low shear-stress events in a turbulent boundary layer

2018

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Simultaneous particle image velocimetry (PIV) and wall-shear-stress sensor measurements were performed to study structures associated with shear-stress events in a flat plate turbulent boundary layer at a Reynolds number Reτ ≈ 4000. The PIV field-of-view covers 8δ (where δ is the boundary layer thickness) along the streamwise direction and captures the entire boundary layer in the wall-normal direction. Simultaneously, wall-shear-stress measurements that capture the large-scale fluctuations were taken using a spanwise array of hot-film skin-friction sensors (spanning 2δ). Based on this combination of measurements, the organization of the conditional wall-normal and streamwise velocity fluctuations (u and v) and of the Reynolds shear-stress (−uv) can be extracted. Conditional averages of the velocity field are computed by dividing the histogram of the large-scale wall-shear-stress fluctuations into four quartiles, each containing 25% of the occurrences. The conditional events corresponding to the extreme quartiles of the histogram (positive and negative) predominantly contribute to a change of velocity profile associated with the large structures and in the modulation of the small-scales. A detailed examination of the Reynolds shear-stress contribution related to each of the four quartiles shows that the flow above a low wall-shearstress event carries a larger amount of Reynolds shear-stress than the other quartiles. The contribution of the small-and large-scales to this observation is discussed based on a scale decomposition of the velocity field.

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“…Three‐dimensional information is obtained by simultaneous recording of multiple views. Details of stereographic and Tomographic‐PIV techniques can be found in the articles of Stanislas and coworkers …”

Section: Introductionmentioning

confidence: 99%

Turbulence statistics and flow structure in fluid flow using particle image velocimetry technique: A review

Ayegba

Edomwonyi‐Otu

2020

Engineering Reports

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Particle image velocimetry (PIV) measurement technique provides an excellent opportunity for investigating instantaneous spatial structures which are not always possible with point measurements techniques like laser Doppler velocimetry. In this review, it was shown that PIV technique provides an effective means of visualizing important structures of Newtonian and drag‐reducing fluid flows. Such structures include large‐scale‐events that constitute an important portion of the Reynolds stress tensor; shear layers of drag‐reducing flows, which have been suggested to constitute the mechanism of drag reduction (DR); and near wall vortices/low speed streaks which constitute the mechanism of turbulence production. PIV investigations of turbulence statistics in Newtonian and drag‐reducing fluid flows were reviewed with the view of providing explanation to DR by additives. Results of turbulence statistics, for Newtonian fluid flow, showed that streamwise velocity fluctuations and turbulence intensity had peak values close to the wall, in a region of high mean velocity gradient, while radial fluctuating velocity and Reynolds stress tensor had peaks further from the wall and at approximately the same detachment from the wall. In single‐ and two‐phase flows in horizontal channels, the velocity profile of polymer solution, in the turbulent regime, show asymmetric behavior. This review highlighted important interfacial characteristics in gas‐liquid flows such as S‐shaped velocity profile as well as the turbulences statistics in each phase and across the interface region. Drag‐reducing agents (DRAs)‐imposed changes on turbulence statistics and flow structures were also examined. PIV studies of drag‐reducing flows showed that DRAs act to dampen wall‐normal‐, streamwise fluctuating velocity, and Reynolds stress tensor. The reduction in Reynolds stress tensor is higher than the reduction of both wall‐normal and streamwise velocity fluctuations and this discrepancy has been associated with the decorrelation of the component of fluctuating velocity. Furthermore, the addition of DRA produces a shift of the peak of wall‐normal velocity fluctuations further from the wall due to increased buffer layer thickness. DRAs do not only act to reduce drag but also to modify the flow structure. The major influence of DRAs on flow structures is seen in the reduced strength and population of vortices close to the wall, increased spacing between low‐speed streaks, reduced frequency of large‐scale events and reduced concentration of small eddies. Effect of DRAs on flow structures depends not only on the level of DR but also on the concentration and molecular weight. The effect of concentration is linked to the elastic properties of the DRA. The influence of DRA on oil‐water flows in similar to its effect on single phase water flow with regards to changes in near wall structures and turbulence statistics. A few research gaps and limitations of the PIV techniques were also highlighted.

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Investigation of the spatio-temporal flow structure in the log-law region of a turbulent boundary layer by means of multi-plane stereo particle image velocimetry

Cited by 11 publications

References 1 publication

Vortical structures in the turbulent boundary layer: a possible route to a universal representation

Vortical structures in the turbulent boundary layer: a possible route to a universal representation

Structure of high and low shear-stress events in a turbulent boundary layer

Turbulence statistics and flow structure in fluid flow using particle image velocimetry technique: A review

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