Flowrate effects on the lateral coalescence of two growing bubbles
Bibliographic record
Abstract
Abstract The coalescence of two growing bubbles presents unique characteristics compared to static bubble coalescence. The gas injection flowrate significantly affects the different stages of bubble evolution, which is poorly understood. In this study, we investigate the flowrate effects on the lateral coalescence of two growing bubbles experimentally. The synchronous bubbling from adjacent needles is achieved using water to push air. During the bubble growth process, we find that the initial nonlinear evolution of bubble volume is because the bubble emerges as a small spherical cap with a large curvature radius and apparent contact angle. As the neck expands after bubble coalescence, the injection flowrate accelerates the neck evolution compared to the case without air injection. We find the neck expansion time decreases linearly with increasing flowrate, while the expansion speed increases with flowrate, but only in the early stage. Moreover, we propose a new theoretical expression that predicts the neck radius well at all the flowrates. At the post‐coalescence oscillation stage, the average projection area of the coalesced bubble increases linearly with time, except for periodic oscillations. Besides, we find that the injected air primarily influences the coalesced bubble's height, which in turn affects the projection area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| 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".