Bibliographic record
Abstract
A novel method of generating secondary droplets using the impaction of a liquid droplet on an orifice plate is proposed. Here, a numerical simulation of this problem is provided using a one fluid volume-of-fluid-based method without considering air in the environment. The impacting droplet may partly spread on the surface of the plate, and partly penetrate through the orifice. The penetrated part may breakup forming a daughter droplet, as well as smaller satellite droplets. The sizes of the generated droplets are related to the volume of the liquid immediately on top of the orifice upon impact. The outcome of the impaction is discussed based on the sizes of the daughter and satellite droplet formed, their velocities, the breakup time, and the breakup length of the penetrated ligament. The influence of the following parameters on the outcome of the impaction is considered: liquid viscosity, liquid surface tension, initial droplet size and velocity, orifice diameter, and the liquid contact angle. A critical Rec number exists for any given We number, under which droplet generation is impossible. Generally, the size of the generated droplet is weakly influenced by the liquid viscosity, and strongly influenced by the liquid surface tension. The size of the daughter droplet increases with the orifice size and reduces with the liquid viscosity, whereas the size of the satellite droplet increases with the viscosity.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".