Investigation of Hydrocyclone Modernization in Küre Copper Ore Regrinding Circuit and Its Effect on Grinding Performance
Bibliographic record
Abstract
After the capacity increase and modernization of the Küre mineral processing plant, the reduction of the particle size led to uncontrollable change in system parameters (pressure, cut size) depending on the grade changes in large diameter hydrocyclones in the re-grinding circuit.Therewithal, the advantages of new generation equipment, which are modernized with developing technologies instead of equipment used in old plants, are important in preventing metallurgical losses.Modern hydrocyclones, can separate more successfully in finer grain sizes.In addition, the need for finer grain size liberalization arises as the grade of the processed ores tends to decrease and the copper minerals in the processed ores have a more complex structure.In this study, samples were taken from ball mill and hydrocyclone unit to determine particle size distribution, hydrocyclone performance, mill performance and mass balance.According to the results obtained from the study, it was decided to modernize the hydrocyclone unit.After the hydrocyclone modernization, simulation studies conducted for different operating conditions to obtain maximum recovery.In the simulation scenarios, apex, hydrocyclone feed percent solids, mill percent solids, hydrocyclone feed pressure parameters were changed to determine optimum conditions and maximize recovery.In conclusion, circuit parameters can be controlled efficiently with lower diameter hydrocyclones.However, higher efficiency has been achieved with the increase in the grinding rate of the closed-circuit ball mill which results in sharper separation of the modernized hydrocyclone unit.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".