Combined Evaporation and Freeze-Thaw Effects in Polymer Amended Mature Fine Tailings
Bibliographic record
Abstract
Evaporation and freeze-thaw phenomena are known to contribute to dewatering and densification of fine tailings streams generated from oil sands bitumen extraction. This thesis reports on studies of 1-Dimensional freezing of polymer-amended mature fine tailings that have different stress histories with respect to degree of desiccation by evaporation and self-weight consolidation. Freezing is accomplished using an electric cooling plate specially mounted in an insulated column. Polymer-amended tailings are placed at a lift of one half-meter, which has been allowed to consolidate. Temperature is recorded using thermocouples, while the densification and dewatering is tracked by monitoring of water content, pore water pressure, and cryo-suctions. After one freezethaw cycle is applied, the samples are cored and then loaded to examine differences in consolidation behaviour post-freezing. Results with respect to dewatering indicate that desiccation and one freeze-thaw cycle enhanced the dewatering process and increased the average solids content of the tailings by 6% when compared to MFT that only underwent consolidation. Also, when comparing the self-weight consolidation and desiccation phases for the three Column Tests, it was found that desiccation increases the efficiency of the freezing process. Lastly, no significant differences in compressibility and permeability properties were found between tailings that underwent just self-weight consolidation and tailings that underwent self-weight consolidation and one freeze-thaw cycle.
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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 | 0.000 |
| 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) | 0.000 | 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 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".