On the entry of cylindrical disks into non-Newtonian fluid mixtures
Bibliographic record
Abstract
A series of laboratory experiments was conducted to investigate solid object characteristics and fluid properties on the free fall of cylindrical disks into stagnant non-Newtonian ambient. The viscosity and yield stress of the ambient fluid mixtures were controlled by adjusting the concentration of a polymer. Six different fluid mixtures were prepared to develop a relatively wide range of fluid viscosities and yield stresses to examine the behavior of free-falling disks in accordance with the variations in the disk's geometry, density, and mixture parameters. The effects of disks’ parameters, such as disk aspect ratio and relative density, on crown formation, pinch-off characteristics, and splash evolution were studied. Experimental results indicated that increasing the disk's density increased the pinch-off depth while a reduction in aspect ratio increased the pinch-off depth. The sinking time diminished with increasing the aspect ratio of disks, and such observations were independent of the rheological characteristics of the fluid mixture. The same devaluation was also experienced for the height of the crown. As the disk's density reduced, the splash curtain became smoother and the waves’ intensity attenuated. The energy losses were found to be correlated with the aspect ratio, density, and fluid viscosity. The augmentation of energy losses was linked with different parameters such as aspect ratio, disk density, and ambient fluid viscosity.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| 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".