Scaling inline static mixers for flocculation of oil sand mature fine tailings
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Bibliographic record
Abstract
Operations to reclaim mature fine tailings (MFT) ponds involve flocculation using high‐molecular‐weight polymers, for which inline static mixers are suited. Three different commercial static mixers were utilized to determine mixing parameters corresponding to optimal dewatering performance of flocculated MFT. MFT was treated with polymer solution under different mixing conditions. The dewatering rates passed through a peak with increasing mean velocity, V and Reynolds number, Re of the fluid. The greater the number of mixer elements, the lower the V and Re at which the peak dewatering rate occurred. Mixing parameters such as G‐value, residence time, and mixing energy dissipation rate of the most rapidly dewatering flocculated MFT were dependent on mixer type and setup. In contrast, peak dewatering rates converged when scaled with respect to specific mixing energy, E, demonstrating that E is a suitable scale‐up parameter for inline static mixing to produce optimally dewatering MFT. © 2015 American Institute of Chemical Engineers AIChE J , 61: 4402–4411, 2015
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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) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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