Critical corrections to models of nonlinear power dissipation of ultrasonically excited bubbles
Bibliographic record
Abstract
Current models for calculating nonlinear power dissipation during the oscillations of acoustically excited bubbles generate non-physical values for the radiation damping (Drd) term for some frequency and pressure regions that include near resonance oscillations. Moreover, the ratio of the dissipated powers significantly deviate from the values that are calculated by the linear model at low amplitude oscillations (acoustic excitation pressure of = P 1 A kPa and expansion ratio of<≊ 1.01). In high amplitude oscillation regimes ( ⩾ P 20 a kPa), the dissipated power due to Drd deviates largely from the dissipated power as calculated by the widely accepted approach that uses the scattered power by the bubbles. We provide critical corrections to the present models. The validity of the results was examined in regimesoflowamplitudeoscillationsandhighamplitudeoscillations.Inthelowamplituderegime,theratioofthedissipatedpowersascalculatedbythecurrentand proposed model were compared with the linear model predictions. At higher amplitude oscillations, the dissipated power by radiation loss as calculated by the current and the proposed models were compared with the dissipated power calculated using the scattered power by the bubbles. We show that non-physical values are absent in the proposed model. Moreover, predictions of the proposed approach are identical to the predictions of the linear model and the dissipated power estimated using the scattered pressure by the bubble. We show that damping due to thermal effects, liquid viscosity and radiation heavily depend on the excitation pressure and that the linear model estimations are not valid even at pressures as low as 20kPa.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".