A multiphase SPH framework for supercooled large droplets dynamics
Bibliographic record
Abstract
Purpose This paper aims to introduce a three-dimensional smoothed particle hydrodynamics (SPH) framework for simulating supercooled large droplets (SLD) dynamics at aeronautical speeds. Design/methodology/approach To include the effects of the surrounding air, a multiphase model capable of handling high density-ratio problems is adopted. A diffusive term is incorporated to smooth the density field and avoid numerical instabilities. Additionally, a particle shifting technique is used to eliminate anisotropic particle distributions. Findings The framework is validated against low-speed droplet impingement experimental results and then applied to the droplet impingement at high speeds typical of SLD conditions. Preliminary parametric studies are conducted to investigate the post-impact splashing. It is observed that a thicker water film can decrease the crown diameter and a smaller impact angle can suppress upward and forward splashing. Originality/value A three-dimensional multiphase SPH framework for SLD dynamics at a wide range of impact speed is developed and validated. The effects of particle resolution, water film thickness and impact angle on the post-impact crown evolution are investigated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".