Detachment of a bubble anchored to a vertical cylindrical surface in quiescent liquid and grid generated turbulence
Bibliographic record
Abstract
Abstract Turbulence plays a critical role in detachment process of bubble from a solid surface. To investigate this effect, detachment process of a stationary air bubble from a nozzle in both quiescent and turbulent liquid field was studied. A stationary vertical (flat‐ended) needle of ID 1.24 mm was used as a nozzle to generate a bubble which was anchored to the needle tip. Different sizes of bubbles were generated in quiescent liquid. Volume and contact angle for these bubbles were measured precisely using microscopic imaging technique and correlated. In the quiescent case experiments, a constant contact angle of 90° and bubble diameter of 3.05 ± 0.004 mm were obtained consistently. A simple force balance approach was proposed assuming bubble in equilibrium to determine this maximum bubble diameter during detachment. The detached bubble size calculated using this approach agreed fairly well with the experimental results. An oscillating grid device capable of operating at different frequencies was then applied to generate a homogeneous, near‐isotropic turbulent velocity field around the anchored bubble. It was observed that for detachment of smaller bubbles, higher turbulence intensity was indeed necessary. The turbulent flow field was quantified using particle image velocimetry (PIV) technique and resolved into flow structures (eddies) of different length scales using a Gaussian filter. It was concluded that smaller eddies perturbed the bubble interface whilst the larger eddies contributed to weakening of the capillary force causing the bubble detachment. Energy dissipation profile obtained from the PIV images indicated significant energy dissipation near the bubble compared to the bulk fluid which supported the fact that strong interactions between bubble and eddies were indeed responsible for bubble detachment.
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 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".