Sustainable design of tailings dams using geotechnical and geomorphic analysis
Bibliographic record
Abstract
Geomorphic landform design for mine waste structures has been proposed as a sustainable alternative to traditional design approaches for decades. Over this time, the focus on mine closure and related sustainability approaches has grown steadily. Many geotechnical engineers and responsible mining companies understand the obligation to design and construct structures that will perform well in the long term. Concepts and tools are provided in this paper that will assist engineers in achieving their long-term goals. This research evaluates four tailings dam designs in terms of their geotechnical stability and long-term geomorphology: two traditional designs (uniform slope and platform-bank) and two geomorphic-inspired designs (catena and horseshoe). All four designs were subjected to two- and three-dimensional (3D) stability analysis, as well as 3D landscape evolution modeling (geomorphic analysis). Results indicated that the horseshoe-style geomorphic tailings dam design performed better than the others for each of the analyses completed. The horseshoe design consisted of interspersed catena slopes and uniform slopes, which resulted in a type of buttressing effect that enhanced the geotechnical stability of the dam while also reducing and focusing surface erosion.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".