Thickener performance variability: underflow solids concentration and flowrate

Abstract

The operational fluctuations of tailings thickeners have the potential to cause significant impacts on the tailings transport system and the tailings deposition at a tailings storage facility (TSF). The statistical analysis of actual recorded data of underflow solids concentration and flowrate of different thickeners is presented in this paper. The collected data are from the operation of four different mines; one Zinc-lead, two Copper and one Gold mine. The variability in these two important parameters can be related to process fluctuations, design or construction defects including instrumentation and controls, the variability in mine orebody during the life of the project or operation of the thickener. The analysis of the data shows that the actual performance of the thickener can be significantly different from what is usually considered at the design stage. An example is presented to show the impacts of thickener performance variability on tailings transport system and thickened tailings beach slope quantitatively.

Paste and Thickened Tailings Transportation Design Aspects Overview

“…The expected variations in the flow and solids concentration for different types of thickener, have been reported in previous research works (Seddon, Pirouz and Javadi, 2018), (Pirouz, Javadi and Seddon, 2017), (Seddon and Fitton, 2011). For the operation of paste thickeners a Coefficient of Variation (C.V.) value between 0.030 and 0.085 is recommended for simulation of underflow solids concentration and mass flowrate variability respectively (Pirouz, Javadi and Seddon, 2017). For High-…”

Stochastic modelling of beach profiles including the influence of thickener performance

“…The normal distribution curves presented by Seddon and Fitton (2011) provided a reasonable fit for solids concentration, but is was recognised that the data for (mass) flow rate of solids was asymmetrical, and the normal distribution did not provide a particularly good fit. The further analysis of subsequent datasets has supported this (Pirouz et al 2017). It would be possible to fit a different mathematical distribution to these data.…”

“…Finally, it should be noted that the method used herein assumes that the underflow solids concentration is independent of the mass flow rate. This has been checked for some, but not all, of the available datasets, and shown to be a reasonable assumption (Pirouz et al 2017).…”

“…Seddon et al (2015) adopted a value of 0.05 in their reported analysis. Incorporation of the additional thickener data (Pirouz et al 2017) has not changed this assessment, which is still considered to be a reasonable estimate for a well operated thickener.…”

“…Seddon et al (2015) adopted an asymmetrical distribution using CV = 0.07 for the top, and CV = 0.12 for the bottom of the range. This is still considered to be representative of 'good' thickener operations (Pirouz et al 2017).…”