Flow fields of particles at very high particle concentrations are important in many scientific and engineering applications, including chemical reactions, petrochemical processing, pharmaceutical ingredient mixing, uranium enrichment, energy conversion, etc.

Despite decades of research and industrial applications, detailed experimental data for the real-time behavior of particles in flows at very high particle concentrations has not existed. One of the reasons is that experimental data is difficult to acquire in such harsh, opaque environments.  Another is that algorithms and software to simultaneously track individual particles at high particle concentrations have not been available.

In this entry for the American Physical Society's (APS) Gallery of Fluid Motion, images of particles in high-speed videos are simultaneously recognized and tracked, even when particle motion is random in both direction and velocity.

Particles are tracked and their trajectories pseudo-colored according to the magnitude of velocity along each trajectory using patented High Speed Particle Tracking Velocimetry (HS-PTV) technology  (US Patents 5333044A Fluorescent Image Tracking Velocimetry and 8391552B1 "Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas")

This technology has been applied to bench-scale, pilot-scale and commercial scale fluidization systems.  Particle motion is measured with excellent spatial and temporal clarity. Data sample rates for velocity vectors along trajectories is in the range of 0.1 to 10 million vectors per second, thereby providing full resolution of the temporal and spatial domains.

High speed videos and HSPTV data have enabled careful study of the real time behavior of gas-particle flow fields. The data and insight from this new technology is proving invaluable for the design and operation of industrial systems using particle flow fields of high particle concentration. It is also proving valuable for the development of computational fluid dynamics (CFD) models of particle flow fields.

The particle tracking technique can also measure gas and fluid flow fields by seeding the flow fields with particles small enough (i.e., that have a low enough Stokes numb6er) to follow the gas/fluid flow.

Particle tracking provides far better spatial resolution than conventional cross-correlation based PIV techniques.

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