Dewatering of Oil Sands Mature Fine Tailings by Dual Polymer Flocculation and Pressure Plate Filtration
Bibliographic record
Abstract
The mature fine tailings (MFT) generated from oil sands operations in northern Alberta, Canada, is the most challenging mine tailings to dewater. The MFT forms a gel structure and takes decades to settle and release water. Dewatering of a MFT sample was investigated in this study with a two-stage polymer treatment protocol followed by pressure plate filtration. MFT treated with polymer pairs consisting of anionic polyacrylamide (A3335) and cationic polyDADMAC (Alcomer 7115) or A3335 and nonionic poly(ethylene oxide) yielded better filtration results than single polymer treatment. Dual polymer treatment led to shorter capillary suction time, higher filter cake solids content, higher net water release, faster water release rate, and lower specific resistance to filtration. The effect of residual bitumen in the MFT on filtration was investigated by comparing the flocculation and pressure filtration of pure kaolinite slurry with and without mixing in 3.0 wt % bitumen centrifuged from MFT. It was found that the addition of bitumen to pure kaolinite decreased the latter’s filterability significantly and that the kaolinite/bitumen mixture had comparable filterability to dual polymer flocculated MFT when treated under the same conditions (i.e., 1000 g/t A3335 and 3000 g/t Alcomer 7115). The addition of bitumen to kaolinite (to 3.0 wt %) also required the polymer dosages to increase by an order of magnitude from pure kaolinite for pressure filtration. It appeared that the additional polymers were consumed in binding and holding the bitumen (to itself and/or to the mineral solids) during the pressure filtration process.
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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 | 0.000 |
| 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) | 0.001 | 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 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".