Study on the distribution of critical liquid bridge length in droplet formation under dripping regime in an annular shear flow field
Bibliographic record
Abstract
Abstract A simplified experimental device was used to simulate the annular shear flow field in a liquid–liquid cyclone reactor, and the formation and break up behaviour of the liquid bridge during the droplet formation under the dripping regime was investigated. Deionized water and fluorescent oil were used as continuous phase and dispersed phase, respectively. The formation and break up process of dispersed phase liquid bridge in the annular simplified experimental device in the dripping regime was captured by camera. The impacts of the ratio of continuous phase velocity to dispersed phase velocity (Vr) and the capillary number (Ca) on the mean critical liquid bridge length (MBL) were analyzed. Furthermore, the functional relationships between MBL and operating parameters (Vr and Ca) under the dripping regime were obtained. The results indicate that the process of droplet formation is mainly affected by viscous force, shear force and surface tension. MBL increases firstly and then decreases with the increase of the two‐phase velocity ratio in dripping regime. Additionally, with the increase of capillary number, MBL decreases.
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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".