Effect of Operating Temperature on Water‐Based Oil Sands Processing
Bibliographic record
Abstract
Abstract Operating temperature is one of the most important controlling parameters in oil sands processing. Considering the massive energy consumption and green house gas emission, lowering the processing temperature is highly desirable. To achieve such an ambitious goal requires a comprehensive understanding on the role of temperature in oil sands processing. This paper provides an overview of major findings from existing studies related to oil sands processing temperature. The relation between temperature and bitumen recovery is discussed. The effect of temperature on the physiochemical properties of oil sand components, such as bitumen viscosity, bitumen surface tension and surface potentials of bitumen and solids, is analyzed. The interactions between bitumen and solids and between bitumen and gas bubbles as a function of temperature are recounted. Also discussed is the role of chemical additives in oil sand processing. It has been found that temperature affects nearly all properties of oil sands among which bitumen viscosity and bitumen‐solids adhesion impose a prominent impact on bitumen recovery. The use of selected chemical additives can reduce bitumen viscosity and/or the bitumen‐solids adhesion, and thus provide a possible way to process oil sands at a low temperature while maintaining a high bitumen recovery.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".