Reliability-based approach to the geotechnical design of tailings dams
Bibliographic record
Abstract
Mine tailings dams are geotechnical structures that are designed to provide adequate and safe storage of tailings materials both during and after the end of mine life. The design of such structures is thus of utmost importance not only to the success of the mining operation, but more importantly to the safety of the surrounding environment such as freshwater resources, wildlife and community developments. This paper presents a reliability-based approach for the geotechnical design of mine tailings dams through a real life case study of a water retention tailings dam. The stability analysis is conducted with a hydromechanical, elasto-plastic finite difference model. The reliability analysis is carried out for three stochastic parameters namely the cohesion and friction angle of the dam core material as well as its hydraulic conductivity. The results are presented in the form of probability distribution functions of the generated factor of safety. The generated reliability indices are compared to target reliability indices to help evaluate the geotechnical design of the dam.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".