The Use of Waste Rock Inclusions to Improve the Seismic Stability of Tailings Impoundments
Bibliographic record
Abstract
Tailings are typically deposited as slurry over an extended period of time. Many types of tailings, such as those from hard rock mines, are fine-grained and cohesionless, making them particularly susceptible to liquefaction. The primary effects of earthquake shaking on tailings impoundments include horizontal loading on the retaining dykes and the development of excess porewater pressures (which may lead to liquefaction) in the retained tailings. Secondary effects can include additional horizontal loading on the dykes due to the strength loss in the tailings and seepage pressures in the dykes due to the dissipation of porewater pressures following shaking. The placement of waste rock within a tailings impoundment to create inclusions of more rigid material could improve the seismic stability of tailings impoundments by providing reinforcement against deformation of the impoundment. Such inclusions can also help dissipate porewater pressures after shaking. The paper presents numerical analyses of a reference tailings impoundment, with and without waste rock inclusions, subjected to a seismic loading and an evaluation of the effects of the inclusions on the dynamic performance of the tailings impoundment.
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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 | 0.001 | 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".