Experimental investigation of bubble size evolution released from a fine bubble ejector
Bibliographic record
Abstract
Abstract The effects of gas flow rate, liquid flow rate, and liquid properties on the bubble size evolution at the outlet zone of an ejector have been investigated systemically. The liquid properties, including surface tension and viscosity, were changed by adding glycerol, ethanol, or Carbopol 2020 into tap water. It was found that increasing the liquid flow rate is beneficial for producing smaller bubbles with a narrower size distribution in the ejector, while the gas flow rate investigated here shows less influence on the generated fine bubble diameter. An intense bubble coalescence phenomenon, which has a negative effect on mass transfer, was first observed at the small outlet zone of the ejector by exploring the bubble size evolution along the axial height. It was found that the mean diameter of the fine bubbles could increase by 48% ~ 90% when they rose only 25 cm from the ejector outlet, and the bubble coalescence could be effectively suppressed by adding a small amount of glycerol to water. The bubble diameter could be reduced by 32% ~ 43% by using a 2 wt.% glycerol solution under the experimental conditions. A comparative study with tap water, glycerol solution, Carbopol solution, and ethanol solution was taken, and the underlying mechanism of reducing the generated bubble size by changing the liquid properties was revealed.
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How this classification was reachedexpand
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)
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 teacher head, 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".