Improved slurry dewatering via process water conditioning: equipment sizing and tailings storage implications
Bibliographic record
Abstract
The potential processing risks associated with the presence of dispersive, swelling clays in mineral orebodies are well known. Uncontrolled dispersion of such clays on contact with water results in problems including poor tailings dewatering and consolidation, increased reagent demand, dirty process water and reduced mineral recoveries and increased plant maintenance with associated economic, environmental and safety implications. Dispersive clays are typically managed via approaches including high dosages of both polymer coagulant and flocculants in thickening, high-pressure secondary dewatering steps such as pressure filtration, belt press filtration or centrifugation, or inline flocculation and deposition of thickened tailings. Commonly, the secondary dewatering step requires re-dosing of additional coagulant and/or flocculant to regenerate a flocculated structure to develop acceptable dewatering rates. An alternative, more proactive approach to managing tailings containing dispersive clays is to promote controlled dispersion of the clays by conditioning the process water circuit to induce a coagulative state in the clays on first contact, reducing clay breakup and ultra-fines generation during initial wetting of the ore on entry to the plant. Clay dispersion control via process water conditioning involves reagent dosing into the process water at only a single location, however, this delivers benefits at every stage of dewatering across the tailings management flow sheet. The potential site-wide benefits of this approach are demonstrated for the ClariVie44®process water conditioner, using a combination of flocculation and settling test results, compression-permeability testwork and pressure filtration model simulations from a range of different tailings samples. The benefits demonstrated include step changes in thickener fines capture and overflow clarity, material improvements in process plant operability and reduced down time due lower fines recirculation, elimination of coagulant dosing in the thickener and downstream secondary dewatering operations, increases in pressure filtration throughputs of up to 300%, improvements in any process technology employing secondary flocculation due to more homogenous structure development, and improved tailings storage facility (TSF) operability and lower risk due to less segregation, faster consolidation and operational dry densities and improved decant water management. Test data from the Jagersfontein kimberlite tailings are also discussed in the context of the recent TSF failure and the potential role of dispersive clays as a risk factor at this site.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".