Comments on F. Pitard’ S “Exploration of the Nugget Effect”

Francois-Bongarcon, D.

doi:10.1007/978-94-011-0824-9_17

Cited by 4 publications

(6 citation statements)

References 6 publications

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“…During sampling breaks, significant variations in the composition and subsequently in the mass fractions measured can take place. This "nugget effect" is a chaotic component and can be considered as the variance of an entirely random component (François-Bongarçon, 1994;Pitard, 1994). Supporting information S16 shows an example of a variation of grain sizes and the mass fraction for one element over time.…”

Section: Samplingmentioning

confidence: 99%

Assessment of element-specific recycling efficiency in WEEE pre-processing

Ueberschaar

Geiping

Zamzow

et al. 2017

Resources, Conservation and Recycling

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Pre-processing is a crucial step to ensure the efficiency of subsequent processes and the quality of recyclates. The efficiency of pre-processing can be affected by high losses to undesignated output fractions. Standard batch tests usually provide mass balances and are a good proxy for bulk materials balances (iron/steel, aluminum, plastics). This article aims at harmonizing methodologies and recommends a strategy for further study in pre-processing on a plant scale. We have developed an “extended batch test” method, which should help to • describe the fates of materials and elements, • assess the quality of output fractions, • identify access points for critical metals and other valuable elements to enable their recovery. A methodical approach was compiled with common material flow analysis methods and an extended set of methods, which improve the reliability via the assessment of uncertainties. This applies to systematic effects and random effects. This extended batch test was performed with a 40 Mg Waste Electrical & Electronic Equipment (WEEE) batch to trace the flows of industrial base metals, precious metals and critical metals in a WEEE pre-processing plant. Results show that one-third of the input was separated and sorted manually, while the remaining material was subsequently crushed and automatically sorted. Copper and precious metals are distributed to various output fractions but are most concentrated in the sorting residues. Critical metals like cobalt and rare earth elements are mainly concentrated in the manually sorted materials but also appear in the ferrous metals scrap and the shredder light fraction

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Section: Samplingmentioning

confidence: 99%

Assessment of element-specific recycling efficiency in WEEE pre-processing

Ueberschaar

Geiping

Zamzow

et al. 2017

Resources, Conservation and Recycling

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“…Some authors have questioned the applicability of TOS and in particular the so-called FSE equation applied to gold (Geelhoed 2011). François-Bongarçon (1998) and François-Bongarçon and Gy (2002) addressed key issues and proposed a modified FSE equation. The modified equation has been applied successfully by practitioners to optimise sampling campaigns (Afewu and Lewis 1998;Cintra et al 2007;Cossio, Noyola, Gonzalez and Espinosa 2004;Dominy and Petersen 2005;Dominy, Platten, Xie and Minnitt 2011;Fallon et al 2012;Pitard 2009).…”

Section: Theory Of Sampling Overviewmentioning

confidence: 99%

“…• what weight of sample should be taken from a larger mass, so that the FSE will not exceed a specified variance; • what is the possible FSE when a sample of a given weight is obtained from a larger lot; and • before a sample of given weight is drawn from a larger lot, what is the degree of crushing or grinding required to lower error to a specified FSE. A technical issue with the use of the FSE equation is the numerical value of the power in the so-called liberation factor (François-Bongarçon 1998;Gy 2004). The problem was addressed by François-Bongarçon (1998), who suggested a modified FSE equation that includes the parameters α and liberation diameter (d λ ) (François-Bongarçon 1998;François-Bongarçon and Gy 2002).…”

Section: Fse Equation and Application To Gold Oresmentioning

confidence: 99%

“…A technical issue with the use of the FSE equation is the numerical value of the power in the so-called liberation factor (François-Bongarçon 1998;Gy 2004). The problem was addressed by François-Bongarçon (1998), who suggested a modified FSE equation that includes the parameters α and liberation diameter (d λ ) (François-Bongarçon 1998;François-Bongarçon and Gy 2002). • grades are relatively low (gram per tonne Au), thus gold particles can be relatively rare 'events' (e.g.…”

Section: Fse Equation and Application To Gold Oresmentioning

confidence: 99%

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Importance of good sampling practice throughout the gold mine value chain

Dominy

2016

Mining Technology

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The mining industry routinely collects samples to assist with decision making, whether for exploration, resource estimation, grade control, or plant design and balances. Poorly designed sampling protocols can result in elevated project risk by increasing variability. Critically, such variability produces both financial and intangible losses. Sample collection, preparation and assay or test work protocols that are optimised to suit the ore type, together with QAQC systems will reduce variability. Many gold deposits display a high natural variability, where the in situ variability can be enhanced by poor sampling practice to yield a high-nugget effect. In this case, specialised protocols are often required. Reporting codes require the Competent Person to consider the quality and implication of sampling programmes. Despite its importance, sampling often does not receive the attention it deserves. In this paper, the importance of good sampling practice is exemplified through a series of case studies, which show the many sampling issues that frequently go unrecognised or unaddressed, resulting in poor decisions and financial loss.

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“…So when Gy introduced the use of the variogram to tackle and analyse the behaviour and sampling of one-dimensional material streams (process), it was with a tool that was not yet fully understood. 4 Decades later, when Francois-Bongarcon established the missing models for the predictive use of the liberation factor, 5,6 it was thanks to a modern understanding of geostatistical concepts.…”

Section: Introductionmentioning

confidence: 99%