Influence of liquid properties on the oblique splashing threshold of drops
Bibliographic record
Abstract
This report investigates how different splashing mechanisms affect the oblique splash threshold of drops impacting a dry solid surface. The splashing behaviors of water, ethanol, and a water/ethylene glycol solution are observed over a wide range of drop diameters (0.7 mm < D < 2.2 mm) and Weber numbers (10 < We < 1040), and several published models are tested in order to predict the thresholds between deposition, one-sided splashing, and two-sided splashing. We found that the splash threshold of liquids that exhibit the corona splashing mechanism can be readily predicted by existing models. However, for liquids such as water that exhibit prompt splashing, the oblique splash threshold is not successfully predicted by any presently established correlation. Hence, our findings identify a critical knowledge gap in the drop impact field, since the behavior of water is of fundamental importance to countless engineering problems. Finally, combining our own results with others reported in the literature, we address some contradictory reports about the influence of liquid viscosity on the splash threshold and demonstrate that the presence or lack of thin-sheet in different experiments could explain the contradictions present in the literature.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".