Droplet impact dynamics on an aluminum spinning disk
Bibliographic record
Abstract
Droplet impact on a spinning surface has been observed in different industries and plays an important role in the performance of industrial systems. In the current study, the dynamics of water droplet impact on a hydrophilic spinning disk is investigated. An experimental setup is designed in a way that droplet diameter, impact velocity, disk rotational speed, and location of impact are precisely controlled. While the droplet diameter is fixed in the present study, other mentioned parameters are changed and their effects on the droplet behavior are discussed. High-speed imaging is used to record the droplet dynamics under various operating conditions. It is demonstrated that after impact, droplet spreads on the surface due to a high adhesion between water and the hydrophilic substrate. It is indicated that the wetted area is a function of time, impact velocity, disk rotational speed, and centrifugal acceleration. Furthermore, depending on the mentioned parameters, different phenomena such as rivulet formation, fingering, and detachment of secondary droplet(s) are observed. In the angular direction, in general, the wetted length increases as time passes. However, in the radial direction, the droplet first spreads on the surface and reaches a maximum value, and then recedes until a plateau is attained. At this instant, a bulk of liquid, which is called wave in this study, moves radially outward from the inner boundary of the droplet toward its outer boundary due to the effect of centrifugal force. Once the wave reaches the outer boundary, depending on its size and momentum, fingers or rivulets are formed, and small droplet(s) may detach. The process is analyzed comprehensively, and different empirical correlations for wetted lengths in radial and angular directions, secondary droplet formation, number of fingers, the onset of fingering, and wave velocity are developed.
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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) | 0.001 | 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".