Bubble Size Distributions for Dispersed Air – Water Flows in a 100 mm Horizontal Pipeline
Bibliographic record
Abstract
Abstract The bubble size distributions of air dispersed in water flowing in a 100 mm horizontal pipeline were studied. Size distributions were obtained with a high‐speed digital camera at axial positions 0.5, 15.3 and 42.3 m from the air injection point. Air was injected into the pipeline through a narrow tube extending into the pipe, perpendicular to the pipe axis. The effects of average water velocity, air concentration, and injection nozzle diameter on the evolution of bubble size distribution with axial pipe position were studied. For the lowest air concentration of 0.07%, equilibrium bubble size distributions were dependent only on water velocity. Nozzle injection diameter did not affect the downstream bubble size distributions at air concentrations of 0.07% and 0.3%. Levich's break‐up theory was found to over‐predict the experimental d max for each test condition.
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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".