Figure 1. A schematic of the basis of stereological error, with sections (gray lines) through liberated and composite particles of varying texture and the corresponding magnitude of bias.
The research objective of this PhD project was to develop mathematical models that will predict the liberation of barren gangue through size reduction of the ore to assess the ores amenability to mineral processing methods such as sorting. An hypothesis was formulated that related ore sortability with gangue liberation through size reduction mechanisms such that the fundamental driver for sortability was the proportion of liberated gangue that could be generated at any given particle size. Since the aim of ore sorting is to reject mass out of an ore stream at the lowest possible metal loss, sorting can only be exploited on ores that generate sufficient quantities of barren gangue at particle sizes suitable for ore sorting technologies e.g. greater than 10 to 20 mm.Three complimentary mathematical models were developed, (one from first principles and two from the existing literature) that used easily measured grade and texture parameters obtained from crushed particles. These models were:1. A refined log-normal distribution model for estimating the particle grade distribution of an ore from measurements of the mean sulphide mineral grade and mode sulphide mineral grade acquired from coarse particles. Having established the three mathematical models, they were then tested and validated with two different data sets. The first data set consisted of mass and assay values for a population of particles obtained from four size fractions sampled from four different ore types. This data was used to model the particle grade distribution of each ore type size fraction. In addition to lognormal modelling, a new sorting potential index was developed that predicts the sortability of an ore based upon the mean grade and mode grade of the Page 3 of 294.particle grade distribution using the refined lognormal modelling methodology outlined in the thesis. The conclusions drawn from this data set may be summarised as follows:1. Lognormal modelling showed that with the exception of two size fractions, the measured particle grade distributions closely followed lognormal statistics which validated the lognormal modelling process that was developed in the thesis.2. Sortability is a direct attribute of the shape of the lognormal distribution with the mode grade determining how many liberated and near liberated gangue particles were present in the distribution whilst the position of the mean grade determined how much inhomogeneity was present in the distribution.3. The distribution with the best properties for sorting had the mode grade positioned near the first grade class within the distribution whilst the mean grade was significantly larger than the mode grade. This ensured that there was abundant liberated or near liberated gangue particle to reject as well as sufficient inhomogeneity to separate higher grade particles from lower grade particles.The second dataset consisted of quantitative mineralogy data obtained from a size by size analysis of a quartz monzonite sampled from a Cu porphyry ore body. The conclusions drawn from...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.