Information about 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.
In order to measure the velocity at least two exposures are needed. They can be recorded on one or several frames.
The frames are 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 (auto-correlation/cross-correlation). 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.
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.
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.
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 will occur with loss of sub pixel resolution. The typical maximum size of the recordable plane is in the region of 10cm to 50cm square, depending on the technology and complexity of the analysis algorithms used.
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.
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.
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 [2] (a Matlab Toolbox), PyPIV [3] (an implementation in Python), OSIV [4] and Gpiv [5] (both implementations in C).
History
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).Technique
Typical PIV apparatus consists of a camera (normally a digital camera in modern systems), a high power laser, for example a double-pulsed Nd-YAG laser laser 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 velocity at least two exposures are needed. They can be recorded on one or several frames.
The frames are 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 (auto-correlation/cross-correlation). 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.
Advantages
The method is to a large degree nonintrusive. The added tracers (if they are properly chosen, see for the reference Melling, 1997 [1]) 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.
Drawbacks
The particles will, due to their higher density, not exactly follow the motion of the fluid (gas/liquid).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.
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 will occur with loss of sub pixel resolution. The typical maximum size of the recordable plane is in the region of 10cm to 50cm square, depending on the technology and complexity of the analysis algorithms used.
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.
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.
Applications
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 [2] (a Matlab Toolbox), PyPIV [3] (an implementation in Python), OSIV [4] and Gpiv [5] (both implementations in C).
See also
- Particle tracking velocimetry
- Laser Doppler velocimetry
- Hot-wire anemometry
- Molecular tagging velocimetry
References
- Particle Image Velocimetry, Raffel M., Willert C. and Kompenhans J. 1998. Heidelberg: Springer-Verlag.''
- 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
- An experimental example — Flow Separation
velocity is defined as the rate of change of position. It is a vector physical quantity, both speed and direction are required to define it. In the SI (metric) system, it is measured in meters per second (m/s). The scalar absolute value (magnitude) of velocity is speed.
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FLUID (Fast Light User Interface Designer) is a graphical editor that is used to produce FLTK source code. FLUID edits and saves its state in text .fl files, which can be edited in a text editor for finer control over display and behavior.
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seeding a flow, or a seeded flow, means to introduce particulates or other foreign substances into an otherwise transparent stream of fluid. These particulates are generally small enough to be carried by the fluid but large enough to be picked up using a flow visualization
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In marine and freshwater ecology, a particle is a small object. Particles can remain in suspension in the ocean or freshwater, however they eventually settle (rate determined by Stokes' law) and accumulate as sediment.
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Flow may refer to:
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- Flow (physics) is the flux times the area. This is the rate at which something travels through a given cross section.
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In physics, dynamics is the branch of classical mechanics that is concerned with the effects of forces on the motion of objects. The former distinguishes it from kinematics and the latter distinguishes it from statics.
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camera is a device used to capture images, as still photographs or as sequences of moving images (movies or videos). The term as well as the modern-day camera evolved from the camera obscura
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digital camera is an electronic device used to capture and store photographs digitally, instead of using photographic film like conventional cameras, or recording images in an analog format to magnetic tape like many video cameras.
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laser is a mechanical device that produces coherent radiation. The term "laser" is an acronym: Light Amplification by Stimulated Emission of Radiation.
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In certain applications, it is advantages to focus light (or image) along one direction but not the direction that is perpendicular to this direction. A cylindrical lens fits this niche.
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An optical fiber (or fibre) is a glass or plastic fiber designed to guide light along its length. Fiber optics is the overlap of applied science and engineering concerned with such optical fibers.
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flash is a device that produces an instantaneous flash of artificial light (typically around 1/3000 of a second) at a color temperature of about 5500K to help illuminate a scene. While flashes can be used for a variety of reasons (e.g.
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In ordinary English, to scatter is to distribute randomly. Scatter also has the following meanings:
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- In physics, scattering is the study of collisions, especially of waves and particles (synonymous in quantum mechanics).
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exposure is the total amount of light allowed to fall on the photographic medium (photographic film or image sensor) during the process of taking a photograph. Exposure is measured in lux seconds, and can be computed from exposure value (EV) and scene luminance.
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A film frame, or just frame, is one of the many single photographic images in a motion picture. The individual frames are separated by frame lines. Normally, 24 frames are needed for one second of film.
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In physics, displacement is the vector that specifies the position of a point or a particle in reference to an origin or to a previous position. The vector directs from the reference point to the current position.
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spatial vector, or simply vector, is a concept characterized by a magnitude and a direction. A vector can be thought of as an arrow in Euclidean space, drawn from an initial point A pointing to a terminal point B.
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Autocorrelation is a mathematical tool used frequently in signal processing for analysing functions or series of values, such as time domain signals. Informally, it is a measure of how well a signal matches a time-shifted version of itself, as a function of the amount of time shift.
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In statistics, the term cross-correlation is sometimes used to refer to the covariance cov(X, Y) between two random vectors X and Y, in order to distinguish that concept from the "covariance" of a random vector X
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A Pitot (IPA: [pito]) tube is a pressure measuring instrument used to measure fluid flow velocity, and more specifically, used to determine the airspeed of an aircraft.
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Flow measurement is the quantification of bulk fluid or gas movement. It can be measured in a variety of ways.
Dependent on the quantity measured different symbols are used. The volumetric flow rate is usually given the symbol and the mass flow rate the symbol .
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Dependent on the quantity measured different symbols are used. The volumetric flow rate is usually given the symbol and the mass flow rate the symbol .
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dimension (Latin, "measured out") is a parameter or measurement required to define the characteristics of an object—i.e., length, width, and height or size and shape.
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In geometry, a cross section is the intersection of a body in 2-dimensional space with a line, or of a body in 3-dimensional space with a plane, etc. More plainly, when cutting an object into slices one gets many parallel cross sections.
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Data processing is any computer process that converts data into information or knowledge. The processing is usually assumed to be automated and running on a computer. Because data are most useful when well-presented and actually informative
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personal computer (PC) is a computer whose original sales price, size, and capabilities make it useful for individuals.
It is unknown who coined the phrase with the intent of a small affordable computing device but John W.
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It is unknown who coined the phrase with the intent of a small affordable computing device but John W.
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real-time computing (RToC) is the study of hardware and software systems which are subject to a "real-time constraint"—i.e., operational deadlines from event to system response.
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pixel (short for picture element, using the common abbreviation "pix" for "pictures") is a single point in a graphic image. Each such information element is not really a dot, nor a square, but an abstract sample.
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Gas is one of the four major states of matter, consisting of freely moving atoms or molecules without a definite shape. Compared to the solid and liquid states of matter a gas has lower density and a lower viscosity.
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Liquid is one of the four principal states of matter. A liquid is a fluid that can freely form a distinct surface at the boundaries of its bulk material.
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Characteristics
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