Houska Based Time-Dependent Rheological Model for Flocculated Tailings
Bibliographic record
Abstract
The rheology of tailings depends on composition and is shear- and time-dependent. Time-dependency might be at the origin of phenomenona such as channel and pattern formation in tailings beaching. Rheology is governed by colloids that form a structure within the fluid. This paper concerns the fitting of the Houska rheological model to controlled stress rheometry data of polymer treated material. The Houska model describes reversible time-dependency, e.g., thixotropy. A novelty here is that irreversible shear down (rheomalaxis) is added to the thixotropy originally captured by the model. The Houska model has the advantage that its time-dependency can be phasewise implemented and tested in numerical codes. In our study, it is shown how the model can be fitted to published detailed controlled shear stress rheometry on flocculated mature fine tailings and is compared with the fitting by a viscosity bifurcation model, which was originally applied. The fits of the viscosity bifurcation model and the current model are comparable. The influence of rheomalaxis on the formation of a lubricating layer in tailings disposal on a beach is investigated by means of a CFD model: flow depth reduces and irregular flow develops.
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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) | 0.001 | 0.000 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".