Air Injection in Water with Different Nozzles
Bibliographic record
Abstract
Air injection systems have a wide range of environmental engineering applications. In this study, we conducted experiments on air injection in a relatively large water tank to investigate the effect of nozzle type, including single/multiple orifice nozzles and a porous airstone, on the characteristics of the bubbles and the induced flow structure. Measurements of bubble characteristics and flow field surrounding the bubble core were obtained using a double-tip optical probe and particle image velocimetry, respectively. The results revealed that bubble velocity did not change significantly with different nozzles, but bubble size decreased significantly while interfacial area, liquid entrainment rate, and kinetic energy of the mean and turbulent flow increased significantly by using the porous airstone instead of nozzles with large orifices. The results for a nozzle with multiple orifices of small diameter are comparable to those for the airstone, which suggests the suitability of its use for systems susceptible to clogging of the pores. Correlations using adequate length and velocity scales are also proposed to describe both bubble and liquid flow characteristics. Finally, applications of the results for different artificial aeration/mixing systems are presented.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".