Particle image velocimetry

Image Analysis:
Particle Image velocimetry
Date:
INSTRUCTOR
DR. MOHSIN SIDDIQUE
ASSIST. PROFESSOR
DEPARTMENT OF CIVIL & ENV ENG.

Image Analysis
 Image analysis is the extraction of meaningful information from images;
mainly from digital images by means of digital image processing techniques.
 Image analysis is used as a fundamental tool for recognizing, differentiating,
and quantifying diverse types of images, including grayscale and color
images (F Mendoza, R Lu 2015).
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 Particle image velocimetry (PIV) is an optical method of flow
visualization used in education and research.
 It is used to obtain instantaneous velocity measurements and related
properties in fluids.
 The fluid is seeded with tracer particles which are assumed to faithfully follow
the flow dynamics.
 The fluid with entrained tracer particles is illuminated so that particles are
visible. The motion of the seeding particles is used to calculate speed and
direction (the velocity field) of the flow being studied.
(Wikipedia, 2020)
Particle image velocimetry (PIV)
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Why PIV?
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Conventional methods
[hot-wire anemometry (HWA) and
laser-doppler anemometry (LDA)]
 Single-point measurement
 Traversing of flow domain
 Time consuming
 Only turbulence statistics
Particle image velocimetry (PIV)
 Whole-field method
 Non-intrusive (seeding)
 Instantaneous flow field
z
After: A.K. Prasad, Lect. Notes short-course on PIV, JMBC 1997

PIV
https://www.youtube.com/watch?v=RGI698OTFrA
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PIV
https://www.youtube.com/watch?v=-O_ii0Yuayg
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PIV
https://www.youtube.com/watch?v=RGI698OTFrA
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PIV
Flow field under waves over movable bed. Mohsin et al. (2010)
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Typical PIV experimental setup
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A typical experimental arrangement for PIV
setup in a wind tunnel
 Basic elements:
Tracer/Seeding particles
Light source (laser)
Image capturing
Synchronizer
Recording hardware (digital
camera)
Image processing
• Note: When digitally recorded video images are used, PIV is termed as DPIV Where
D acronym for Digital
• With the increasing power of computers and widespread use of CCD cameras, DPIV
has become increasingly common, to the point that it is the primary technique today.

 Typical PIV apparatus consists of:
a camera (normally a digital camera with a CCD chip in modern systems),
a laser with an optical arrangement to limit the physical region illuminated
(normally a cylindrical lens to convert a light beam to a line/sheet),
a synchronizer to act as an external trigger for control of the camera and
laser, the seeding particles and the fluid under investigation.
PIV software/program is used to post-process the images
PIV Experimental setup
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 Non-intrusive velocity measurement
 Indirect velocity measurement
 Whole field technique
 Velocity lag
 Illumination
 Duration of illumination pulse
 Time delay between illumination pulses
 Distribution of tracer particles in the flow
 Density of tracer particle images
Main Features of PIV
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 Number of components of the velocity vector
 Extension of the observation volume
 Temporal resolution
 Spatial resolution
 Repeatability of evaluation
Main Features of PIV
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Reading assignment: Page 5 to 8 of the following reference:
Raffel, M., Willert, C. E., Wereley, S. T., Kompenhans, J. (2007) “Particle Image
Velocimetry-A Practical Guide” Springer-Verlag. 2nd Edition

 The seeding particles are an inherently critical component of the PIV system.
 Depending on the fluid under investigation, the particles must be able to
match the fluid properties reasonably well.
 Otherwise they will not follow the flow satisfactorily enough for the PIV
analysis to be considered accurate.
 Ideal particles will have the same density as the fluid system being used, and
are spherical (these particles are called microspheres).
Basic Elements-Seeding/tracer particles
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Basic Elements-Seeding/tracer particles
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 Lasers are predominant due to
their ability to produce high-power
light beams with short pulse
durations.
 This yields short exposure times for
each frame.
Basic Elements-Light source
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• Nd:YAG lasers, commonly used in PIV setups, emit primarily at 1064 nm
wavelength and its harmonics (532, 266, etc.) For safety reasons, the laser
emission is typically bandpass filtered to isolate the 532 nm harmonics (this
is green light, the only harmonic able to be seen by the naked eye).
• The optics consist of a spherical lens and cylindrical lens combination. The
cylindrical lens expands the laser into a plane while the spherical lens
compresses the plane into a thin sheet.

 Laser can be classified into:
Continuous wave (CW) lasers or,
more optimally, pulsed lasers
 CW lasers deliver energy on a continuous basis and pulsing’ is obtained by
either chopping or sweeping the beam
Basic Elements-Light source
Energy vs. time emitted from a laser. a) typical continuous wave (CW)
laser; constant energy over time. b) CW laser 'chopped' with a shutter
mechanism. [ref. Craig Brideau, P. Stys (2009)]
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 The PIV recording modes (image capturing) can be classified into two main
categories:
(1) methods which capture the illuminated flow on to a single frame and
(2) methods which provide a single illuminated image for each illumination
pulse.
 These branches are referred to as “single frame/multi-exposure PIV” and
“multi-frame/single exposure PIV” respectively
Basic Elements-Image Capturing
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Basic Elements-Image Capturing
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 The most commonly used electronic image sensors are:
 Charge coupled devices, or CCD, charge injection devices (CID) and
 Complementary metaloxide semiconductor (CMOS) devices
Basic Elements-Recording hardware
A typical camera for PIV
Source: https://www.phantomhighspeed.com/products/cameras/veo/veo640
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Fig. 4.9. Timing diagrams for PIV recording based on various types of CCD
sensors.
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 The limitation of typical cameras is that its fast speed is limited to a pair of
shots. This is because each pair of shots must be transferred to the computer
before another pair of shots can be taken.
 Typical cameras can only take a pair of shots at a much slower speed.
 Faster digital cameras (high-speed cameras ) using CCD or CMOS chips
were developed since then that can capture two frames at high speed with a
few hundred neno-second difference between the frames.
 High-speed cameras allow for total synchronization of multiple imaging
angles and of the lasers or lighting being used to illuminate the experiment.
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 Image processing: The main concepts are already covered in previous
lectures
 Note: processing or preprocessing does not always lead to accuracy
 Image Analysis: The focus will be on the following topic:
Cross-correlations algorithm for PIV
Basic Elements-Image processing & analysis
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 Digital Spatial Correlation in PIV Evaluation
Cross-correlation algorithm: It is a commonly used algorithm to compute
the displacement of particles. The following equation computes the cross-
correlation between images:
The variables I and I' are the samples (e.g. intensity values) as extracted from the
images where I' is larger than the template I. Essentially the template I is linearly
‘shifted’ around in the sample I' without extending over edges of I'.
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at T=t at T=t+1
Search window reading of group of particles at give
location at T=t in interrogation window to find out
their location in interrogation widow at T=t+1
Cross Correlation algorithm
• For shift values at which the samples’
particle images align with each other,
the sum of the products of pixel
intensities will be larger than elsewhere,
resulting in a high cross-correlation
value RII at this position.
• The highest value in the correlation
plane can then be used as a direct
estimate of the particle image
displacement
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• For shift values at which the samples’ particle images align with each other, the
sum of the products of pixel intensities will be larger than elsewhere, resulting
in a high cross-correlation value RII at this position.
• The highest value in the correlation plane can then be used as a direct estimate
of the particle image displacement.
• The particle velocities are then calculated as function of displacement (S) and
the frame rate (Δt) i.e. V=S/Δt
Cross-correlation of images for PIV
Image Ref. Brossard et al. 2009: Principles and Applications of Particle Image Velocimetry
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Removal of Noise:
Comparison of Horizontal and
vertical velocity measured by ADV
and computed by PIV (After FFT) PIV computations Before and
After FFT
Fast Fourier
Transform
High Freq Noise
Arising from miss-matching of search window at T=t+1
Cross Correlation algorithm
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Comments….
Questions….
Suggestions….
References:
Raffel, M., Willert, C. E., Wereley, S. T., Kompenhans, J. (2007) “Particle Image
Velocimetry-A Practical Guide” Springer-Verlag. 2nd Edition
https://en.wikipedia.org/wiki/Particle_image_velocimetry
https://velocimetry.net/application.htm
http://www.pivchallenge.org/
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Thank you !

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