Particle flow fields of high particle concentration are found in many commercial applications, including chemical processing, energy conversion, pharmaceutical processing, food processing, and biomedical applications. This technology will allow, for the first time, the measurement of particle motion within high particle concentration fields.
Using a novel Candidate Trajectory Tree Process, this technology overcomes well-known problems — such as correspondence ambiguity, crossing trajectories, and loss of images — that are common to video sequences of large numbers of objects at high object concentrations. For each object image, a tree of candidate trajectories is formed using extrapolative search techniques. Search areas of novel size and shape are formed based on Newtonian properties of motion such as velocity and acceleration. The search areas range from minimum sizes that first detect slower-moving objects, to a maximum size that detects the fastest objects.
A fast, accurate computational framework has also been developed. The software has proven to be computationally quick and precise on a wide range of particle flow applications. This software technology reads raw video sequences and automatically produces data for object motion, including object velocities, trajectories, and concentrations. The data is in the form of two-dimensional maps of velocity and concentration for each camera frame. High-speed videos with up to 40 million particle images over 200,000 video frames have been analyzed in minutes or hours on personal computers, and up to 1,000 particle images have been simultaneously tracked through hundreds of video frames. Additionally, the software has accurately tracked high concentrations of particles undergoing purely random motion, similar to Brownian motion.
Thus far, the technology has been primarily used to measure and analyze single-phase fluid motion (using tracer particle) and multiphase particle motion with high particle concentrations. The technology has successfully mapped particle motion at very high particle concentrations in circulating fluidized beds at several laboratories. In another application, the technology mapped the turbulent motion of blood analog fluids around a 4-mm-diameter turbine spinning at 20,000 rpm in a medical device. Fluid flow undergoing cavitation has been mapped in a water tunnel. This technology was also used by the Unified Command Flow Rate Technical Group to estimate the amount of oil leaking from the Deepwater Horizon Macando Well in the Gulf of Mexico. The technology allowed researchers to estimate oil flow rate by tracking hydrate particles and vortical flow structures in the oil leak jets.
This technology can also be used to extend the well-known, double-frame (or double image) particle image velocimetry (PIV) technology to analyze fluid motion through thousands of video frames (sometimes called time resolved PIV). It also has been used with small-diameter (less than 0.5"-diameter) borescopes to probe into opaque, high-concentration flow fields.
This method of simultaneously tracking high numbers of objects at high object concentrations offers the following benefits. The method is computationally fast because it overcomes the computational explosion caused by the well-known “correspondence ambiguity” problem inherent in prior methods of object tracking. It overcomes the problem of trajectory crossing and image loss common to tracking high numbers of objects, and tracks objects or particles in highly concentrated, dense flow fields, which was not possible before. The technology can be applied to single-phase flows to measure fluid motion by seeding fluids or gases with tracer particles, and can track large numbers of any type of object, provided that object locations are available at consecutive time increments.
Applications exist in a wide range of industrial, environmental, and medical challenges, and wherever object tracking is essential.
For more information, contact Jessica Sosenko at