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Particle Engineering Research Center (PERC)

Development of the Efficient Rotating Cone Classifier

Many industrial members of the Particle Engineering Research Center (PERC) at the University of Florida need a particle classifier in order to produce particle streams within a narrow range of size variation. Particle size affects properties such as texture, performance, flow-ability, or taste of the finished product. Research at PERC had previously focused on the Boundary Layer Momentum Transfer (BLMT) classifier because it provided the great advantage of minimizing loss (attrition) of fragile particles. However, this process had limitations in producing smaller particles and poor "sharpness" of the particle cuts.

In search of a better classifier, PERC researchers developed a new design, the Efficient Rotating Cone (ERC) classifier. The new classifier changes the way that feed particles enter the classification zone of the device, an innovation that reduces particle attrition. Obtained data show good cut sharpness and easy control of the particle size by adjusting the rotational speed of the device, which is an advantage over the BLMT classifier.

Most importantly, the PERC ERC classifier is capable of separating the particles before they enter the classifier. The ultimate deliverable of this project is a new type of particle classifier that gives sharper cuts, causes less attrition, and costs less to manufacture and purchase than existing classifiers. Computational fluid dynamics modeling of the classifier will provide a tool for improving classifier design and for predicting and optimizing performance based on classifier geometry and operating conditions. The PERC classifier will provide member companies with a means to classify their powders for a wide range of cut sizes at industrial-scale throughputs. Industry is closely collaborating with the Center's investigators in the development and testing of this new classifier.

To learn more about this topic:
Visit the Particle Engineering Research Center research page at http://www.erc.ufl.edu/research/

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Photo 300x222.

Chart 275x212. Classifier Yields. Sharp  and Controllable Cut Size.

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Last modified: February 22, 2005