Design and evaluation of mixtures of mine waste rock and tailings
Bibliographic record
Abstract
The technique of mixing mine waste rock and tailings for disposal has the potential to avoid the problems of acid rock drainage and tailings liquefaction. This paper presents a rational basis for the design of mixtures based on particle packing theory and laboratory investigations. Mixtures were conceptualized using a particle model that allows mixture design and interpretation of behaviour. Laboratory investigations included examination of tailings rheology, mixture trials, and compressibility testing of waste rock, tailings, and mixtures of waste rock and tailings. Results indicate that mixture design governs mixture structure, and consequently also compressibility behaviour. A method is presented to predict mixture compressibility from mixture ratio and the properties of the parent waste rock and tailings. The study provides theory for the design and evaluation of mixtures as a mine waste disposal technique and demonstrates that the design of geotechnical properties is possible for homogeneous mixtures of mine wastes at the laboratory scale.Key words: co-disposal, particle packing, rheology, compressibility, waste rock, tailings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".