Time-dependent rheological behaviour of cemented backfill mixture
Bibliographic record
Abstract
When cemented backfill mixture (CBM) is transported through pipelines from a backfill plant to stopes, it experiences shearing forces over the transport time. In this paper, the effects of solids concentration, binder content, shear rate and curing time on the time-dependent rheological behaviour of CBM were studied. It was found that over long periods of shearing at a constant rate greater than 5 s−1, the shear stress decreased at first and then increased gradually with time. When the shear rate was less than 0.5 s−1, shear stress increased slightly firstly with shearing time, then it started to behave similar to the test with a higher shear rate whose shear stress decreased firstly and then increased. The samples that were sheared at a higher shear rate exhibited a lower apparent viscosity and the higher yield stress CBM samples displayed more pronounced shear-thinning properties. It was also found that for transient flow, increasing the solids concentration and the curing time lead to both a higher initial shear stress (τ0) and minimum shear stress (τmin). When the cement to tailings ratio increased, the τ0, τmin and final shear stress after shearing for 3600 s (τ3600) increased at first, and then subsequently decreased. Moreover, changes in the solids concentration profile and the cement hydration property were displayed during the rheological tests.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".