A mathematical model for predicting classification performance in wet fine screens

Screening is a well-known classification process in the minerals processing industry. The process involves separation of fine particles from coarse particles based on size and is applicable to both dry and fine screening. Fine screening is normally carried out wet. Until recently, fine wet screening had been limited to relatively low throughput applications. Developments in the recent past have seen the evolution of fine screening to high capacity applications. It has found application in operations such as closed circuits with a mill in place of hydrocyclones. However, even though developments are increasing, there has been a process model developmental lag. A fine wet screen model that can be used for unit simulation purposes to predict screen performance outcomes or integration into other models to simulate and predict process performance is necessary. Most existing screen models are for dry and coarse screening applications. This thesis is aimed at developing a fine wet screen process model for predicting wet screening performance in the 45 - 150 μm range. Pilot plant testwork was conducted using a UG2-Chrome ore blend as feed.

Grantor dc:publisher.institution

Department of Chemical Engineering

Year dc:date.issued

2015

Author dc:creator

• Mwale, Adolph Ntaja

Advisors dc:contributor.advisor

• Mainza, Aubrey Njema
• Kallon, Daramy
• Bepswa, Aaron Paul

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/20122

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/20122