Evaluating a hydraulic classification system for the differential separation of solid mixtures

A hydraulic classification system having four equidistant discharge points for solid mixtures was evaluated using a 23 factorial experimental design for each discharge. The evaluation factors consisted of 0.9 to 2.7 m3/h flow rate, 1,420 to 2,520 Kg/m3 particle density and 0.0005 to 0.002 m particle...

Full description

Saved in:
Bibliographic Details
Published inIngeniería e investigación Vol. 29; no. 3; pp. 36 - 41
Main Authors Osorio Correa, Adriana Marcela, Marín, Juan Miguel, Peláez Restrepo, Juan Felipe, Restrepo Vásquez, Gloria María
Format Journal Article
LanguageEnglish
Published Bogota Universidad Nacional de Colombia 01.09.2009
Online AccessGet full text

Cover

Loading…
More Information
Summary:A hydraulic classification system having four equidistant discharge points for solid mixtures was evaluated using a 23 factorial experimental design for each discharge. The evaluation factors consisted of 0.9 to 2.7 m3/h flow rate, 1,420 to 2,520 Kg/m3 particle density and 0.0005 to 0.002 m particle size. The response variable was the degree of each material's recovery efficiency. Stat Graphics statistical software was used for obtaining the theoretical models, showing higher than 99% correlation between them. The theoretical models were experimentally validated for two cases: classifying different sized material having the same density and classifying materials having equal size but different density. Coal and quartz were the materials used for the model; they were characterised in terms of their propertied as individual particles and as a mass of particles. Size separation was done by sieve (granulometric) analysis. Error percentages were low (0.7% to 14%) in the first experimental case; however, errors in the second case in predicting the separation of heavier material were very high (above 50%), perhaps due to the nature of the material. The above models will form the basis for continuing to study these operating and design variables which in practice determine such processes' dynamic response and operational performance for the ongoing search for optimum operating conditions.
ISSN:0120-5609
2248-8723
DOI:10.15446/ing.investig.v29n3.15180