2015
DOI: 10.17580/gzh.2015.12.02
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Ore strength analysis in planning ore pretreatment circuit

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Cited by 3 publications
(3 citation statements)
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“…Statistical estimates of the studied parameters are presented in Table 1 [6][7][8]. In the analysis of the source data, there is considerable variability in the extraction of precious metals: gold is in the range of 23-95% (the content of metal in the ore is 0.4-2.1 g/t), silver in the range of 20-88% (the content of metal in the ore is 4.3-55.3 g/t) [9] The correlation matrix for the studied array is presented in Table 2. The correlation matrix shows a negative correlation between the content of precious metals in the ore and their extraction into the copper concentrate [10,11].…”
Section: Main Part 21 Multiple Regression Equationmentioning
confidence: 99%
“…Statistical estimates of the studied parameters are presented in Table 1 [6][7][8]. In the analysis of the source data, there is considerable variability in the extraction of precious metals: gold is in the range of 23-95% (the content of metal in the ore is 0.4-2.1 g/t), silver in the range of 20-88% (the content of metal in the ore is 4.3-55.3 g/t) [9] The correlation matrix for the studied array is presented in Table 2. The correlation matrix shows a negative correlation between the content of precious metals in the ore and their extraction into the copper concentrate [10,11].…”
Section: Main Part 21 Multiple Regression Equationmentioning
confidence: 99%
“…The selection and sizing of the main technological equipment units for minerals comminution circuits is usually based on the required capacity, on the physical and mechanical properties of minerals, and on the required size distribution of the initial and final products of grinding [1][2][3]. The physical and mechanical properties of the ore can be described using different methods [4][5][6]. In Russia, the ore grinding calculations use the specific mill volumetric capacity by design size fraction (usually -0.074 mm) [7,8].…”
Section: Introductionmentioning
confidence: 99%
“…The mutual infl uence of particles is also signifi cant, especially noticeable at high concentrations. Meanwhile, it was found that at the output of the chopping cutter (especially at large aggregate volumes), different size classes hada similar shape (and as a consequence, the shape ratio), so the infl uence of the shape in the criterion output can be neglected [6,7]. Mill drain usually contains intergrown pieces in the entire range of their unlocking (from ρ max to ρ min ) and size, then the selectivity ratio for unlocking intergrown pieces φ can be calculated from the expression: here λ is the volume content of a mineral with a density of p max or p min .…”
Section: Introductionmentioning
confidence: 99%