Contribution of desiccation to monotonic and cyclic strength of thickened gold tailings – not the same as over-consolidation
Bibliographic record
Abstract
In many jurisdictions, regulators are concerned with remobilisation of high unbounded deposits of mine waste residuals, such as thickened tailings stacks. Consequently, the monotonic and cyclic behaviour of thickened tailings is of significant interest to practitioners of mine waste geotechnique. Thickened tailings are known to gain strength through a combination of hindered settling, desiccation, and consolidation post-deposition. This paper reports on the effects of over-consolidation ratio (OCR) and desiccation, investigated using a simple shear apparatus (NGI type). Samples for element testing were obtained from laboratory tests simulating multilayer deposition in columns or flumes. In each test, tailings were deposited at some initial solids concentration and allowed to desiccate to different values of water content, both above and below the shrinkage limit. These tailings were then overlaid with fresh tailings, and allowed to resaturate by capillary action from the fresh layer. Tailings from the bottom layer were then extracted using thin-wall Shelby tube. Some tailings were allowed to settle, subsequently extracted with no desiccation, and mechanically over-consolidated. Very sharp differences in both the quantitative and qualitative behaviours of samples prepared by these two methods were observed. Mechanically over-consolidated samples exhibited high peak strengths, whereas desiccated samples exhibited much lower strengths at phase transformation, but substantial strain hardening past phase transformation. This information is very important to geotechnical practitioners working on thickened tailings projects, as many operate under the assumption that desiccation is analogous to mechanical over-consolidation.
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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".