Jetting onset on a liquid surface accelerated past a submerged cylinder
Bibliographic record
Abstract
A novel experiment is presented to study the initial disturbances on a free surface due to the constant acceleration of liquid around a submerged obstacle. The surface response to different obstacle sizes, initial surface heights and fluid velocities is measured using high-speed videography. Perturbations observed on the surface are classified into either jetting or gravity waves by measuring the steepness of growing liquid columns. A classification phase map between these two regimes is obtained and compared with analytical results by Martín Pardo and Nedić (2021). The agreement between decision boundaries is good for high Froude numbers (high fluid velocities) but deteriorates at lower velocities, where viscosity and surface tension effects (not considered in the analytical model) have a greater predominance. The surface profile and perturbation amplitude measured in experiments are also compared against this analytical model. In all cases, the model accurately predicts the corresponding experimental results at the beginning of the motion, but the prediction error increases with time. It is also observed that faster moving surfaces that lead to the onset of jetting have greater prediction accuracies and longer validity times of the predictions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".