Particle image velocimetry

Particle image velocimetry

Particle image velocimetry (PIV) is an optical method used to measure velocities and related properties in fluids. The fluid is seeded with particles which, for the purposes of PIV, are generally assumed to faithfully follow the flow dynamics. It is the motion of these seeding particles that is used to calculate velocity information.


For a recent overview of the history of PIV technique see: Adrian, R.J., "Twenty years of particle image velocimetry". "Experiments in Fluids" 39:159–169 (2005).


Typical PIV apparatus consists of a camera (normally a digital camera in modern systems), a high power laser, for example a double-pulsed or a copper vapour laser, an optical arrangement to convert the laser output light to a light sheet (normally using a cylindrical lens), and the fluid/gas under investigation. A fibre optic cable often connects the laser to the cylindrical lens setup. The laser acts as a photographic flash for the digital camera, and the particles in the fluid scatter the light. It is this scattered light that is detected by the camera.

In order to measure the fluid's velocity, at least two separate exposures must be recorded. This typically involves producing a pair of laser pulses which are recorded onto a pair of camera frames (specialised PIV cameras are able to record two frames with as little as 100 ns between them). It is also possible to record both pulses onto the same frame (thereby enabling the use of a less expensive camera), but these multiply-exposed images must be analysed using auto-correlation, rather than cross-correlation, and this approach tends to produce slightly less accurate results.

The frames are next split in a large number of interrogation areas, often called tiles. It is then possible to calculate a displacement vector for each tile with help of signal processing. This is converted to a velocity using the time between image exposures.

Timing electronics allows one to control the spacing between image exposures. The electronics also permits image pairs to be acquired at various times along the flow. These digital delay and pulse generators provide several outputs that can be delayed and referenced to each other.

If there is in house PIV expertise and time to develop a system, even though it is not trivial, it is possible to build a custom PIV system. Research grade PIV systems do, however, have high power lasers and high end camera specifications for being able to take measurements with the broadest spectrum of experiments required in research. If, for example, you want to spend less money, of course you get less resolution and lower framerates. There are also PIV analysis software available in the open source community. The results can have similar or even better quality compared to the expensive commercial PIV systems.


The method is to a large degree nonintrusive. The added tracers (if they are properly chosen [Melling, 1997 [] ] ) generally cause negligible distortion of the fluid flow.

Optical measurement avoids the need for Pitot tubes, hotwires or other intrusive Flow measurement probes. Additionally the method is capable of measuring an entire two-dimensional cross section (geometry) of the flow field simultaneously.

High speed data processing allows the generation of large numbers of image pairs which, on a modern personal computer may be analysed in real time or at a later time. Thus a high quantity of near continuous information may be gained.

Sub pixel displacement values allow a high degree of accuracy, since each vector is the statistical average for many particles within a particular tile. Displacement can typically be accurate down to 10% of one pixel on the image plane.


In some cases the particles will, due to their higher density, not exactly follow the motion of the fluid (gas/liquid). If experiments are done e.g. in water, it is easily possible to find very cheap particles (e.g. plastic powder with a diameter of ~60µm) with the same density as water. If the density still does not fit, the density of the fluid can be tuned by increasing/ decreasing its temperature. This leads to slight changes in the Reynolds number, so the fluid velocity or the size of the experimental object has to be changed to account for this.

Particle image velocimetry methods will in general not be able to measure components along the z-axis (towards to/away from the camera). These components might not only be missed, they might also introduce an interference in the data for the x/y-components. Some new methods also allow to measure three-dimensional flow though.

The size of the recordable flow field is limited by the size of the tracer particles. The scattered light from each particle should be in the region of 2 to 4 pixels across on the image. If too large an area is recorded, particle image size drops and peak locking might occur with loss of sub pixel precision. There are methods to overcome the peak-locking effect, but they require some additional work. PIV can measure fields of roughly 5mm*5mm (with very small particles and a macro lens) up to several square meters.

Since the resulting velocity vectors are based on cross-correlating the intensity distributions over small areas of the flow, the resulting velocity field is a spatially averaged representation of the actual velocity field. This obviously has consequences for the accuracy of spatial derivatives of the velocity field, vorticity, and spatial correlation functions that are often derived from PIV velocity fields.

Commercial research grade PIV systems include a Class IV laser and high resolution/speed digital camera that make the systems potentially unsafe and very expensive. Commercial systems are prohibitively expensive (around US$100K) and potentially not safe to use in teaching.

Improvements to basic PIV

Each of the above limitations have been addressed by specialist techniques. For example, a similar velocimetry method known as molecular tagging velocimetry, or MTV, uses molecule sized tags, which are often already a part of the flow. Small molecules being much closer to the size and density of a flow minimize the error of particles not following the flow. One example used in humid air flows uses a laser to dissociate the water (H2O) in the flow into H + OH. The hydroxyl (OH) molecule serves as the tag. This method is known as hydroxyl tagging velocimetry (HTV).

Stereoscopic PIV utilises two cameras with separate viewing angles to extract the z-axis velocity component. Holographic PIV similarly extracts the third component. However Both these techniques drastically increase cost and complexity of the system.

Recent research has outlined the possibility of treating the flow images as a continuous system of flow structures, instead of a system of quasi-random points. This allows the imaging of a limitless size of flow field, provided appropriate seeding is ensured.

The molecules used as tracers in MTV are subject to Brownian motion. This limits the method to ultra-high speed flows. A typical example of the successful application of MTV is the investigation the intake flow in engines. Here the spray is very dense and flow speeds are high enough to allow accurate results for MTV.

The effect of the spatial averaging can be reduced by the use of more complicated algorithms based on deforming the interrogation areas or based on Particle tracking velocimetry using PIV as an initial estimate for the position where individual particles are advected.

Because of safety concerns and the typically high price, PIV has only occasionally been used as part of fluid mechanics teaching. Recently introduced systems from Interactive Flow Studies [] and Etalon Research [] , are however both safe and affordable enough to be used within a teaching environment.


PIV has been applied to a wide range of flow problems, varying from the flow over an aircraft wing in a wind tunnel to vortex formation in prosthetic heart valves. Though less common, PIV can also be used for quantifying the deformation and motion of solid materials and tissues that have embedded markers or are in some other way visually heterogeneous (e.g. using fluorescent speckles or particle grains).

Rudimentary PIV algorithms based on cross-correlation can be implemented in a matter of hours, while more sophisticated algorithms may require a significant investment of time. Several open source implementations are available including URAPIV [] and mpiv [] (a Matlab Toolbox), PyPIV [] (an implementation in Python), JPIV [] (a Java implementation), OSIV [] and Gpiv [] (both implementations in C).

Recently Interactive Flow Studies introduced an Educational PIV (e-PIV) system that is used in teaching fluid mechanics to students studying fluid mechanics in design, engineering and science including physiology. The development of the system is funded by the National Science Foundation (NSF). The advantage of this system is that it is affordable, safe, easy to use and versatile.

ee also

*Particle tracking velocimetry
*Laser Doppler velocimetry
*Hot-wire anemometry
*Molecular tagging velocimetry


*"Particle Image Velocimetry: A Practical Guide", Raffel M., Willert C. and Kompenhans J. 1998. Heidelberg: Springer-Verlag. ISBN 3540636838
*"Digital Particle Image Velocimetry — Theory and Application", Westerweel, J. 1993. Delft: Delft University Press. []

External links

* [ from "The Art of Laser Velocimetry"] , an explanation of DPIV, and an [ explanation of holographic PIV] .
* [ Acoustic Particle-Image Velocimetry — Development and Applications]
* [ Educational Particle Image Velocimetry (e-PIV) - resources and demonstrations]
* [ Matlab PIV toolbox]
* [ OpenPIV]

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