Effect of cementitious amendment on the hydrogeological behavior of a surface paste tailings’ disposal
Bibliographic record
Abstract
Abstract Surface paste disposal (SPD) can be considered as an effective alternative technique for mine waste management. The technique consists of first removing upstream water (by thickening and/or filtration) from tailings, then depositing them at the surface in a paste-like state. These techniques allow for the recycling of water, limit risks related to the failure of dikes, and favor progressive mine site rehabilitation. However, there are, thus far, only a few studies on the environmental behavior of tailings deposited using the SPD technique. To evaluate the hydrogeological and geochemical behaviors of a sulphidic tailings’ deposit simulating the SPD method, a laboratory study was performed using a physical model. Paste tailings were prepared and deposited inside the physical model in nine layers. In the first stage, only the first two bottom layers were amended with cement (2 % w/w of PC10 Portland cement). The physical model was then subjected to wetting and drying cycles, and the water collected after each flush was analysed for chemistry and its volume was measured. At the end of the 27th cycle, a tenth layer of cemented tailings was deposited on the top of the tailings’ stack. Testing was performed for 34 cycles, and then, the model was dismantled and the collected samples were analysed through a multidisciplinary fine characterisation. The results of this investigation showed that the volume of collected water at the bottom of the physical model varied over the test’s duration. This could be due to seasonal variations in the temperature and moisture of the laboratory. The cemented layer deposited on the top of the physical model appears to play the role of protecting against underlying layers from evaporation. Finally, diffuse oxidation that progressed along the preferential pathway was observed.
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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 | 0.000 |
| 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) | 0.001 | 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".