Boiling during high-velocity impact of water droplets on a hot stainless steel surface
Bibliographic record
Abstract
High-velocity impact of water droplets (0.55 mm diameter) on a heated stainless steel surface was photographed. To achieve high impact velocities, the test surface was mounted on the rim of a rotating flywheel, giving linear velocities of up to 50 m s −1 . Two cartridge heaters were inserted in the substrate and used to vary substrate temperature. A charge coupled device (CCD) video camera was used to photograph droplets impinging on the substrate. To photograph different stages of droplet impact, the ejection of a single droplet was synchronized with the position of the rotating flywheel and triggering of the camera. Substrate temperature was varied from 100 to 240 °C and the impact velocity from 10 to 30 m s −1 . High-resolution photographs were taken of vapour bubbles nucleating sites inside the thin liquid films produced by spreading droplets. An analytical expression was derived for the amount of superheat required for vapour bubble nucleation as a function of the impact velocity. For a given surface roughness, the amount of superheat needed decreased with impact velocity, which agreed with experimental results. For a fixed impact velocity, the maximum extent of droplet spread increased with substrate temperature.
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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) | 0.002 | 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".