Effect of particle size on the rheology of Athabasca clay suspensions
Bibliographic record
Abstract
Abstract The success of the separation process conventionally used in Alberta for oil sands extraction is highly influenced by the rheology of the oil sands slurry. In the gravity separation vessel, high slurry viscosities can hinder the rise of aerated bitumen and reduce the efficiency of the recovery process. In this study, the effect of particle size on the viscosity of oil sands slurries is investigated. Solids from mature fine tails (MFT) obtained from tailings pond were fractionated into three fractions of different particle size distributions and their rheological properties were studied. The solids in each fraction were characterized by XRD analysis which showed the presence of different types of clays in each fraction. For the rheological measurements, dispersions of the three fractions were prepared in the supernatant water decanted from centrifuged MFT to maintain the solution chemistry of the solids. Suspensions of each fraction showed a non‐Newtonian shear thinning behaviour as well as yield stress that is characteristic of structure formation within the suspensions. For all solids fractions, increasing solids concentration led to higher viscosities and higher yield stress values. Viscoelastic properties of the suspensions showed stronger solid‐like behaviour at higher particle concentrations. Among the three fractions numbered from 1 to 3, solids in fraction 3 were coated with organic matters, exhibiting the highest suspension viscosities. Also for fraction 3, higher gelling potency was observed at much lower weight fractions of solids as compared to the other fractions.
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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 | 0.000 | 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 | 0.000 |
| 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".