Characterizing binary droplet collisions of power‐law fluids
Bibliographic record
Abstract
Abstract This study focuses on the dynamics of two equal‐sized droplets of non‐Newtonian liquids with simulations using the volume of fluid method and the local front reconstruction method. The non‐Newtonian behavior is implement via a power‐law model. The droplet interactions are performed for Weber numbers ranging from 20 to 300 and impact parameters from 0 to 0.6. Both methods produce similar results at low Weber numbers, while the disintegration of the droplets at high Weber numbers occurs via different mechanisms. Our results demonstrate that the boundaries of the collision maps are highly dependent on the power‐law index. Additionally, the diameter of the ring for head‐on collisions is increased with increasing Weber number and decreasing power‐law index, while the critical ligament length in off‐center collisions increases with Weber number and power‐law index.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".