Hybrid Quasi Molecular-Continuum Modeling of Supercooled Large Droplet Dynamics for In-flight Icing Conditions
Bibliographic record
Abstract
A mesoscale model for droplet dynamics based on a quasi-molecular approach is proposed. It considers the interaction between quasi-molecules within a single liquid droplet, each quasi-molecule representing an agglomeration of a large number of actual water molecules. The goal is to improve the understanding of the dynamics of large droplets collisions over dry or wet surfaces at velocities typical of aeronautical applications. This detailed analysis will eventually be used to refine the macroscopic Eulerian description of the water impingement process by providing numerical correlations for splashing and bouncing phenomena. Approaches for extracting macroscopic quantities such as temperature and transport coefficients from the quasi-molecular method are discussed. A proper choice of the free parameter of the model that leads to accurate values of the macroscopic properties is also addressed. To model the droplet impingement process more accurately, the quasimolecular approach is then coupled with a continuum flow solver in order to include the droplet deformation effects due to the external airflow.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".