EVALUATING UNCERTAINTY OF LABORATORY-SCALE PARTICLE SORTING AMENABILITY TESTS

2019

Christopher Baxter, National Research Council of Canada; Andriy Plugatyr, National Research Council of Canada; Francis Vanier, National Research Council Canada; Sevan Bedrossian, National Research Council of Canada

Amenability of crushed ore to particle sorting is commonly assessed using a relatively small number of rocks. In this study, Monte-Carlo simulations were carried out to investigate the effect of constitutional heterogeneity of a lot of a particulate material on uncertainty in estimated mass pull – recovery curves as a function of the number rocks used for testing. The obtained results indicate that sample size has a significant effect on uncertainty estimates for material with a high constitutional heterogeneity. Thus, under examined conditions, absolute deviations from both the expected recovery and mass pull values of ±10-15% (at 95% CI) were obtained when using a 100 rock sample size. Recommendations to improve current methodologies for bench-scale particle sorting amenability testing are provided.
Keywords: Particle sorting, amenability, heterogeneity, uncertainty, Monte-Carlo simulation
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