Investigation of near wall wake induced aeroacoustic noise by simultaneous use of particle image velocimetry, microphones and wall pressure sensors

2011 ◽  
Vol 1 (3/4) ◽  
pp. 337
Author(s):  
T. Ruiz ◽  
J. Boree ◽  
C. Sicot ◽  
L E. Brizzi ◽  
Y. Gervais
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Pressure Sensors ◽  
Wall Pressure ◽  
Aeroacoustic Noise ◽  
Image Velocimetry ◽  
Simultaneous Use ◽  
Near Wall

Particle image velocimetry investigation of a turbulent boundary layer manipulated by spanwise wall oscillations

2002 ◽  
Vol 467 ◽  
pp. 41-56 ◽  
Author(s):  
GAETANO MARIA DI CICCA ◽  
GAETANO IUSO ◽  
PIER GIORGIO SPAZZINI ◽  
MICHELE ONORATO
Keyword(s):  
Boundary Layer ◽  
Particle Image Velocimetry ◽  
Turbulent Boundary Layer ◽  
Particle Image ◽  
Oscillation Amplitude ◽  
Research Programme ◽  
Oscillation Period ◽  
Wall Turbulence ◽  
Image Velocimetry ◽  
Near Wall

Particle image velocimetry has been applied to the study of a canonical turbulent boundary layer and to a turbulent boundary layer forced by transversal wall oscillations. This work is part of the research programme at the Politecnico di Torino aerodynamic laboratory with the objective of investigating the response of near-wall turbulence to external perturbations. Results are presented for the optimum oscillation period of 100 viscous time units and for an oscillation amplitude of 320 viscous units. As expected, turbulent velocity fluctuations are considerably reduced by the wall oscillations. Particle image velocimetry has allowed comparisons between the canonical and forced flows in an attempt to find the physical mechanisms by which the wall oscillation influences the near-wall organized motions.

Some Experience on Particle Image Velocimetry of Near-Wall Shear Layers at Subsonic Velocities

2010 ◽  
Vol 5 (2) ◽  
pp. 55-68
Author(s):  
Andrey V. Boiko Boiko ◽  
Vasily N. Gorev ◽  
Aleksandr V. Dovgal ◽  
Aleksandr M. Sorokin ◽  
Hein Stefan ◽  
...  
Keyword(s):  
Experimental Data ◽  
Particle Image Velocimetry ◽  
Particle Image ◽  
Shear Layers ◽  
Linear Instability ◽  
Wind Tunnel Testing ◽  
Mean Velocity ◽  
Separating Flow ◽  
Image Velocimetry ◽  
Near Wall

Experimental data on linear instability of the laminar separating flow and mean velocity characteristics of the turbulent boundary layer are reported. The results are obtained through wind-tunnel testing of Particle Image Velocimetry (PIV) performed at DLR, Goettingen. Details of the method, as applied to the above problems of fluid mechanics, are considered. The present findings seem helpful during experimental work on subsonic near-wall layers, when focusing on their instantaneous and time-mean velocity characteristics.

Investigation of aeroacoustic noise generation by simultaneous particle image velocimetry and microphone measurements

2008 ◽  
Vol 45 (6) ◽  
pp. 1073-1085 ◽  
Author(s):  
Arne Henning ◽  
Kristian Kaepernick ◽  
Klaus Ehrenfried ◽  
Lars Koop ◽  
Andreas Dillmann
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Noise Generation ◽  
Aeroacoustic Noise ◽  
Image Velocimetry

Influence of Inertial Particles on Turbulence Characteristics in Outer and Near Wall Flow as Revealed With High Resolution Particle Image Velocimetry

2016 ◽  
Vol 138 (9) ◽  
Author(s):  
Ammar Saber ◽  
T. Staffan Lundström ◽  
J. Gunnar I. Hellström
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Volume Fraction ◽  
Spherical Particles ◽  
Normal Velocity ◽  
Inertial Particles ◽  
Mean Flow ◽  
Turbulent Characteristics ◽  
Image Velocimetry ◽  
Near Wall

A fully developed turbulent particle-gas flow in a rectangular horizontal channel 100 × 10 × 4000 mm3 is disclosed with high spatial resolution two-dimensional (2D) particle image velocimetry (PIV). The objective is to increase the knowledge of the mechanisms behind alterations in turbulent characteristics when adding two sets of relatively large solid spherical particles with mean diameters of 525 and 755 μm and particle size distributions of 450–600 and 710–800 μm, respectively. Reynolds numbers are 4000 and 5600 and relatively high volume fraction of 5.4 × 10−4 and 8.0 × 10−4 are tested. Both the near wall turbulent boundary layer flow and outer core flow are considered. Results show that the carrier phase turbulent intensities increase with the volume fraction of the inertial particles. The overall mean flow velocity is affected when adding the particles but only to a minor extent. Near the wall, averaged velocity decreases while fluctuating velocity components increase when particles are added to the flow. Quadrant analysis shows the importance of sweep near the wall and ejection events in the region defined by y+ > 20. In conclusion, high inertia particles can enhance turbulence even at relatively low particle Reynolds number <90. In the near bottom wall region, particles tend to be a source of instability reflected as enhancement in rms values of the normal velocity component.

Experimental Measurements in Near-Wall Regions by Particle Image Velocimetry (PIV)

2014 ◽  
Author(s):  
Puxuan Li ◽  
Steve J. Eckels ◽  
Garrett W. Mann ◽  
Ning Zhang
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Particle Density ◽  
Piv Measurements ◽  
Experimental Fluid Mechanics ◽  
Micro Piv ◽  
Piv Measurement ◽  
Image Velocimetry ◽  
Eddy Structures ◽  
Near Wall

The current study investigates the flow field near a surface with a micro-PIV system using a square tube to enhance optical access. Measurements of velocity fields and eddy structures near the wall of tubes are important to the design of in-tube surface geometries. In experimental fluid mechanics, particle image velocimetry (PIV) is now a common way to measure velocity. However, PIV measurements near walls require efforts to deal with low particle density, high shear gradient and wall reflection. The current paper discusses a PIV measurement technique utilized to observe flow dynamics in near-wall regions. PIV uncertainty analysis is discussed in this study. The experimental results are compared with previous results for validation.

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