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A detailed quantification of the phenotypes indicates a graded variability within a requirement for posterior development.
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Using this methodology one can evaluate, within a certain time period, the expected grade variability for various pile sizes as well as the internal grade variability when a given pile is reclaimed.
Grade Engineering® spans a range of operational techniques that exploits intrinsic grade variability to remove low grade uneconomic material prior to energy intensive and inefficient grinding.
The methodology proposed here combines longitudinal piles and geostatistical simulations to emulate the in situ variability as well as the reclaimed pile grade variability.
Various methods are used when designing homogenization piles, and most fail to incorporate the in situ grade variability that is intrinsic to the mineral deposit.
It is also demonstrated that the internal grade variability decreases for a given pile size, when the number of layers in the pile is increased.
This paper evaluates a novel combination of geostatistical simulation and a blending pile emulator in predicting in situ grades variability and planning blending piles.
The grade variability was classified in each mineralized zones defined by the SS N and C V models, based on which tonnage cut-off models were generated.
However, in size-based coarse separation the efficiency relies on having a processing stream with a strong grade variability across size fractions (i.e. high grade by size response) and therefore a high RR value.
This suggests that the cut-off grade for those metals should be above 100 ppm and points to the critical aspect of metal grade variability in the micaceous residue as a major issue if potential industrial applications are to be considered.
Pathological sampling can reveal cytoplasmic and nuclear grade variability within the same tumour, whereas specific clones are found using DNA sequencing techniques (Kanamaru et al, 1996).
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