Simulation-aided studies of heavy-media separation in Angouran lead and zinc ore

Karami E., Harzanagh A. A., Moradkhani D., Mozaffari E.

SEPARATION SCIENCE AND TECHNOLOGY, vol.55, no.2, pp.386-393, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 55 Issue: 2
  • Publication Date: 2020
  • Doi Number: 10.1080/01496395.2019.1575416
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Agricultural & Environmental Science Database, Analytical Abstracts, Applied Science & Technology Source, Biotechnology Research Abstracts, Chimica, Communication Abstracts, Compendex, INSPEC, Metadex, Pollution Abstracts, DIALNET, Civil Engineering Abstracts
  • Page Numbers: pp.386-393
  • Hacettepe University Affiliated: Yes


Pre-concentration of lead and zinc ore in Calcimin (public Co) which is done using heavy-medium cyclones (HMC) undergoes lots of inefficiencies and not in the desired manner. Considering the fact that feed material is variable in the case of Zn-Pb grades, it is important to make HMC plant flexible when facing different ore types. The present study aims to prepare a predicting tool which can determine the operational parameters of HMC plant such as density separation and predict the properties of the final product e.g. Zn-Pb grades and recoveries using existing models. After determining the feed ore characterizations including particle size distribution, XRF, XRD, and high-density sink-float tests, an existing empirical model for high-density HMC was used. Inserting the data obtained from ore characterization tests in existing models and solving necessary calculations makes it possible to predict the behavior of HMC plant at different ore types and select the most favorable operational conditions without doing a mass of experimental work. An optimal flowsheet of HMC plant was proposed as an example for the studied sample which shows the possibility of producing a pre-concentrate with Zn and Pb grades of 36.60 and 3.24%, respectively, with the recoveries of 93.66 and 90.31%.