Droplet impact dynamics on a rotating aluminum disk: Comparative study based on liquid properties
Bibliographic record
Abstract
An experimental study has been conducted to explore the effect of liquid properties on the dynamics of a droplet impacting a rotating aluminum disk. The study focuses on water, ethanol, and a glycerol–water mixture to cover a wide range of Weber, Reynolds, and Ohnesorge numbers as well as contact angles. The investigation has identified four distinct regimes, including deposition, child droplet formation, asymmetric splash, and partial rebound, depending on the rotational speed, impact velocity, and liquid properties. The angular and radial spreading lengths of droplets at different operating conditions and times have been measured and different empirical correlations have been developed to link these lengths as well as the maximum radial and angular spreading lengths to the Reynolds (or Weber) number, the Ohnesorge number, dimensionless time, and contact angle hysteresis. It is revealed that the angular spreading length markedly increases with time and rotational speed. Conversely, an increase in the Ohnesorge number leads to a reduction in the angular spreading. The maximum radial spreading length diminishes with a decrease in impact velocity or an increase in the Ohnesorge number or the rotational speed. Additionally, it has been observed that within the deposition regime, as the Ohnesorge number increases or the contact angle decreases, the droplet does not retract radially. Upon droplet deposition on the rotating surface, it has been noted that a wave propagates across the droplet surface from its inner edge to the outer edge, leading to the formation of fingers. Remarkably, it has been determined that the velocity of this wave is unaffected by liquid properties and is solely determined by the rotational speed and impact velocity. Furthermore, a substantial increase in the number of fingers is observed with a decrease in the Ohnesorge number or an increase in the rotational speed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".