Local and overall gas holdup in an aerated coaxial mixing system containing a non‐<scp>Newtonian</scp> fluid
Bibliographic record
Abstract
Abstract Gas dispersion in non‐Newtonian fluids is a challenging task due to the formation of large cavities behind the impeller blades, which leads to the generation of very large bubbles. In this study, the effects of impeller speed, impeller type, pumping direction, and CMC concentration on the local and overall gas holdup inside a coaxial mixing tank comprised of two central impellers and an anchor were investigated through tomography, computational fluid dynamics (CFD), and response surface methodology (RSM). The results showed that an increase in the fluid apparent viscosity resulted in decreasing the gas holdup except for the pitched blade impeller in upward‐pumping mode. Although the highest overall gas holdup was accomplished for the downward pumping and co‐rotating mode, the local gas holdup data revealed a non‐uniform distribution of gas by this configuration. The lowest gas dispersion efficiency was achieved by a system comprised of two Scaba impellers and an anchor.
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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".