Bibliographic record
Abstract
The effects of high intensity ultrasound field in water and the resulting volume oscillations of one underwater micron-sized gas bubble initially resting between two larger but micron-sized solid particles are numerically studied. The model assumes that the two particles remain at rest while the bubble changes its shape in the presence of the particles. Specifically, this study predicts the bubble’s expansion, collapse, and interaction effects with the adjacent two solid spherical particles which are not necessarily of equal size. The model assumes that the flow surrounding the bubble and two particles is incompressible. A 2-D Finite Element method which is capable of tracking the ultra fast moving boundary of the bubble is developed and an associated computer program is written to solve the modeled equations and boundary conditions. In the absence of a similar study in the literature, the validation (although not shown here) of the numerical method is carried out by solving the expansion and collapse of a single bubble initially resting in an infinite extent of fluid for which theoretical results are well-known in the literature. A good agreement is obtained between the numerical and theoretical results [18]. Numerical results for the temporal shapes of the bubble, its lifetimes for various parametric cases are provided and discussed. The variations of the pressure and the velocity fields in the liquid surrounding the bubble and two particles are also analyzed and discussed.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".