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Cyclone Control

Cyclones are gas-solid separation devices characterised by low investment and operating costs, which have been used in the API industries for valuable product recovery (1). The simulation of reverse-flow cyclones has been the subject of several different approaches (2), but none of the proposed theories is capable of consistently giving good predictions when applied to predicting experimental grade-collections obtained with different geometries, operating conditions and particle-size distributions. Of all these, the Mothes and Loffler model (3) gives predictions which are better correlated with available data (2,4,5). However, the model predictions are dependent on the knowledge of the particle’s turbulent dispersion coefficient, which depends on operating conditions, cyclone geometry and particle size. These difficulties have led cyclone designers to base their geometries on empirical testing, such that a widely accepted basic rule to succeed in cyclone design is to use only geometries that have been experimentally tested (6).

Since each cyclone manufacturer has its own high efficiency (HE) design, the question of which design is indeed better for a particular application is relevant. Also, it is highly unlikely that the optimum design can be found by empirical testing, as there are too many design parameters involved. This has been experimentally confirmed by Maa et al, who tried to improve spray-dryer recovery using re-designed cyclones (1). Despite various attempts at re-designing the cyclones, no improvement could be observed for capturing particles below about 2μm, and severe losses (up to 20 per cent) were observed.

In a previous paper, optimisation problems were formulated for maximising cyclone collection and a ratio of costeffectiveness (7). The problems included several constraints on geometry, pressure drop and saltation velocity, thus ensuring that feasible cyclones with efficiencies near the design efficiency could be obtained. The solution to one of these problems was demonstrated in laboratory, pilot and full-scale tests to be superior to other high-efficiency designs available on the marketplace and in the scientific literature (7-10).

Recognising that particle physical properties (size, specific gravity, porosity) and concentration play a very important role in particle capture in cyclones, a computer program was recently developed, coupling the agglomeration model of Ho and Sommerfeld (11) with the Mothes and Loffler (3) or the Salcedo et al (10) model of particle capture respectively.

 


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Romualdo Salcedo has a Chemical Engineering degree from the University of Porto, Portugal (1975) and Masters (1977) and PhD (1981) degrees from McGill University, Montreal, Canada. Currently a Professor of Chemical Engineering and Chair of the Doctoral Program in Chemical and Biological Engineering at the University of Porto, he is Chief Technology Officer and co-founder of Advanced Cyclone Systems. His mains interests involve research on global optimisation and on its application to the optimised design of air pollution control equipment, in particular for the capture of very fine particles using cyclone systems. Email: romualdo@acsystems.pt

Júlio Paiva has a Chemical Engineering Degree from the University of Porto, Portugal (2006). After that, he worked for a short period as a technical engineer in a Project of Biofuels. He is currently finishing his PhD in Biological and Chemical Engineering at the University of Porto. His research involves modelling innovative cyclone systems and the development of the PACYC computer model for fine particle capture taking into account particle agglomeration in cyclone systems. Email: julio.paiva@fe.up.pt

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Romualdo Salcedo
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Júlio Paiva
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