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Record W3158514403 · doi:10.82308/14509

Effect of operating variables in Knelson Concentrators: a pilot-scale study

2010· article· en· W3158514403 on OpenAlexfundaboutno aff
Sunil Kumar Koppalkar

Bibliographic record

VenueeScholarship@McGill (McGill) · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsnot available
FundersGoldcorpMcGill University
KeywordsScale (ratio)Environmental scienceGeographyCartography

Abstract

fetched live from OpenAlex

Knelson concentrators are the most widely used semi-continuous centrifuge separators for the recovery of gold and platinum minerals by gravity methods. Bench scale characterization studies on these units provide information about the occurrence of gold in ore samples (e.g. gold particle size distribution, amount of gold recoverable by gravity) but not about the effect of operating variables for full-scale units such as top size of particle, feed rate, fluidization flow rate and rotation speed. Such work is not easily performed online on full-scale units owing to the inevitable variations in feed quality and to the impossibility of varying operating parameters systematically in the face of production requirements. To attack the problem, a pilot plant comprising a 12-in CD Knelson concentrator, a feed screen and tailing sump-pump arrangement was installed in the grinding-B circuit of Dome Mine, Porcupine Joint Venture (PJV), now Porcupine mine, Goldcorp Inc. Timmins, Ontario. The pilot plant received a bleed from the feed to the full-scale units. The pilot facility was extensively sampled in two campaigns. Fifteen tests were conducted in the first campaign and another sixteen in the second. In all 31 pilot tests, twenty six 30-minute recovery cycle tests, called "short tests" and five, 90-minute recovery cycle tests, dubbed "long tests", were conducted. Measuring recovery was the focus of the "short tests"; measuring the deterioration of recovery over time was the focus of the "long tests". The sampling protocols were designed accordingly. Detailed metallurgical balances were made to analyze the effect of operating and design variables on the performance of 12-in pilot Knelson Concentrator as a step towards understanding full-size units and to study the mechanism of concentrate bed erosion. To gain some fundamental information about the recovery mechanism of the Knelson concentrator, percolation of dense particles in a gangue bed was investigated using a fluidized bed column in the gravitational field. Metallurgical results indicate that operating conditions including feed rate, rotation velocity, fluidization water flow rates and top feed particle size have little impact on the shape of the recovery compared to feed size distribution. A particle size hypothesis was tested using relevant industrial Knelson concentrator data. The analysis showed that a relatively coarse feed would impact negatively on the recovery between 106 and 425 µm. On the other hand, it would make it easier to recover particles between 25 and 106 µm. A finer feed would have a bigger impact on recovery around 25 to 106 µm and would yield a GRG recovery that decreases monotonically with the decreasing of particle size. This would be linked to the natural resistance offered by the gangue particles to the percolation of gold particles, which is significant at a particle size where the gangue is most abundant. The flowing slurry may be compared to a dynamic screen, with openings roughly the order of magnitude of the dominant particle size. This finding is useful for the simulation of the Knelson units, which uses the typical recovery curve "decreasing recovery with decreasing particle size" for estimating gravity recovery and it was thought that the shape of the curve had no impact on the estimation. Now, with this finding, either the fine or coarse recovery curve will be used depending on the size distribution of the gravity circuit feed. For example, for a coarse target grind, the coarse curve could be used and, for a fine target grind, the fine curve could be used.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.254
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2010
Admission routes2
Has abstractyes

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