Cavitation onset in an impulsively accelerated liquid column
Bibliographic record
Abstract
This paper introduces a novel piston-driven apparatus to study the onset of cavitation in an impulsively accelerated liquid column as it compresses a closed gas volume. The experiment is monitored using high-speed videography and piezoelectric pressure transducers. Cavitation onset is observed in the liquid column as it undergoes an abrupt deceleration and is associated with a sudden drop in pressure in the liquid that leads to negative pressure (tension). A novel numerical modeling approach is introduced where the liquid column is treated as a spring-mass system. This approach can reproduce compressibility effects in the liquid column and is used to investigate the wave dynamics responsible for the onset of tension and cavitation in the liquid column. The model is formulated as a coupled set of non-linear differential equations that reproduce the dynamics of an experiment while capturing the pressure wave activity in the liquid column. A parametric study is conducted experimentally and numerically to investigate the behavior behind the onset of cavitation. The mechanism for the onset of cavitation is identified as a series of wave reflections at the boundaries of the liquid column, and this mechanism is found to be well reproduced by the model. While a traditional cavitation number criterion is shown to be unable to predict cavitation onset in our experiment, our numerical model is found to correctly predict the onset of cavitation for a wide range of experimental parameters.
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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 | 0.001 |
| 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".