Rheology for deposition control and deposit failure risk analysis
Bibliographic record
Abstract
Application of rheology to the post-deposition behaviour of tailings is important for the design of the slope of the impoundment, control of layering for purposes of strength enhancement through desiccation, properly describing the mixing of different tailings streams and for dam breach consequence analysis. This paper aims to advance the understanding of tailings rheology in the post-deposition context to aid all of these applications. Firstly, thixotropy and its quantitative implications for beach slope and layer geometry are explored using a simple treatment. Secondly, method dependency in yield stress measurement is discussed, along with how such uncertainty can be practically handled by considering the appropriate stress path and timescale for a particular application. Finally, numerical simulation using a thixotropic rheology of channel flow down a beach and runout from a dam breach experiment, conducted in a centrifuge, is used to highlight the utility of advanced rheology to such problems. The paper uses data collected from published work on both hard rock and oil sands tailings over the last 15 years.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 0.001 |
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".