Eulerian Modeling of Supercooled Large Droplet Splashing and Bouncing
Bibliographic record
Abstract
A conservative Eulerian numerical approach for modeling postimpact Supercooled Large Droplets undergoing splashing and bouncing on aircraft surfaces is presented. The approach introduces the effect of the postimpact droplets by successive solutions of the conservation equations. Two models have been selected to identify the droplet splashing and bouncing conditions, and to provide initial conditions for the reinjected water. The method has been applied to droplet impingement in Supercooled Large Droplet conditions on clean and iced NACA 23012 geometries, as well as the MS(1)-0317 airfoil, and the results have been compared to experimental data. Good agreement is observed for both impingement limits and collection efficiency. Additionally, the method has been applied to a three-element high-lift configuration operating in one of the proposed Appendix O Supercooled Large Droplet environments to demonstrate the danger posed by the re-impingement of splashing and bouncing droplets on complex interacting aerod...
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".