Bibliographic record
Abstract
The motion of long bubbles in tubular capillaries has typically been described by bulk characteristics. However, the dynamics of slug bubbles in square capillaries are more complex due to a corner flow and a thin film flow. The physics can be correctly explained by elucidating local 3D features of the two-phase flow field. To this aim, an experimental study based on particle tracking velocimetry (PTV) and a numerical simulation based on the volume-of-fluid method were conducted to investigate the dynamics of slug bubbles rising in a flowing square capillary with a cross-sectional area of 3 × 3 mm2. To precisely analyze the phases' interaction, interfacial flow data were mapped onto a radial-tangential coordinate system on central and diagonal planes. The simulated interface topology and velocity fields show a good agreement with the experimental PTV data on the central plane, with an absolute error of less than 1.2% for terminal bubble speed. Tangential speeds show their maxima occurring in the channel corners, where pressure is maximum. The thin liquid film flow that occurs where the bubble approaches the wall applies noticeable shear stress on the channel walls, where high and low-pressure regions are generated. Structures of vortices inside the bubble were identified using isosurfaces of the Q-criterion, and their cores were detected based on the parallel vector method. Results reveal a dominant vortex ring adjacent to the liquid film flow and two oblique vortex tubes close to the bubble's nose.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.250 | 0.455 |
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".