Bending and growth of entrained air filament under converging and asymmetric rotational fields
Bibliographic record
Abstract
Here we have proposed the increase of the entrainment rate by extruding an air filament under the action of convergent but asymmetric rotational field. By varying the source speed and the diameter of rotational fields, we showed the bending of an air filament towards the higher strength direction of the asymmetric inertia. Interfacial profiles like bubble ejection from the air filament and non-collapsible entrainment with air accumulation in a stagnant zone are obtained in finite volume based numerical simulations, on gradual increase of average rotational fields. Physical understanding of bent interface profile reveals the presence of multiple stages in filament growth depending upon the inertia of surrounding medium. Accumulation of air in the stagnant zone is found to be more prominent in case of rotational speed based asymmetry in contrast to its counterpart having diametric asymmetry of imposing sources. Relative comparison between these two methods of producing asymmetric field showed faster growth of filament upon varying the source diameter, while keeping the speed same. In case of extreme retardation and enhancement of rotational asymmetry, film pinch off and formation of bubble train have been reported. The shape of ejected bubbles is governed by the inertia of the surrounding medium, and bubbles have taken elliptical shapes with their major axis aligned parallel to the adjacent velocity field.
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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 | 0.000 | 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 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".