Concurrent Droplet Coalescence and Solidification on Surfaces With Various Wettabilities
Bibliographic record
Abstract
An experimental study is performed to analyze the shear driven droplet shedding on cold substrates with different airflow speeds typical of those in the flight conditions. Understanding the mechanism of simultaneous droplet shedding, coalescence, and solidification is crucial to devise solutions for mitigating aircraft in-flight icing. To mimic this scenario, the experimental setup is designed to generate shear flow as high as 90 m/s. The droplet shedding at high-speed is investigated on a cold surface (0 and −5 °C) of different wettabilities ranging from hydrophilic to superhydrophobic. Result analyses indicate that on a hydrophilic substrate, the droplets form a rivulet, which then freezes on the cold plate. In contrast, on the superhydrophobic surface, there is no rivulet formation. Instead, droplets roll over the substrate and detach from it under the effect of high shear flow.
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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".