Power Demand and Mixing Performance of Coaxial Mixers in Non-Newtonian Fluids
Bibliographic record
Abstract
Experiments have been carried out in a transparent dished bottom stirred tank with a diameter T of 0.48 m and liquid level of 0.6T. The power consumption and mixing performance of a coaxial mixer consisting of a wall-scraping anchor and different inner dispersion impellers (Rushton turbine, 45° pitched blade turbine and CBY) operating in inner impeller-only, co- and counter-rotating modes have been experimentally characterized in viscous Non-Newtonian fluids (2% and 3% w/w CMC solutions) with different rheology behaviors. The results show that, for the co-rotating modes, the power consumption of the anchor could decrease up to 5% of that for the anchor rotating-only mode, whereas for the counter-rotating dispersion modes, it could increase to two times of that for the anchor rotating-only. However, the power consumption of the inner impellers is almost independent of the anchor rotation. We propose new correlations to give better fitted power curves between the generalized Reynolds number and the power number by considering not only the impeller geometry and the characteristic speed, but also the speed ratio. For each coaxial mixer, one reasonable power curve can be generated for different experimental speed ratios and different rotation modes. Impellers in co-rotating mode are more efficient than the inner impeller-only and the counter-rotating modes in the mixing of non-Newtonian fluids. Among the above three dispersion impellers, the power consumption of the CBY-anchor combination is the lowest compared with those for the other two combinations giving the similar mixing performance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".