Development of a nonlinear model for the pressure dependent attenuation and sound speed in a bubbly liquid and its experimental validation
Bibliographic record
Abstract
Presence of the MBs in the sound field increases the attenuation of the medium and changes the sound speed. A detailed knowledge about the attenuation of the medium is critical for controlling and optimizing the behavior of the MBs in applications. However, existing models of ultrasound attenuation in bubbly mediums are based on linear approximations (low amplitude MB oscillations) and thus are not valid in many regimes used in applications. A model to calculate the nonlinear attenuation and sound speed is developed by deriving the complex and real part of the wave number from the Calfish model. The predictions of the model were validated by measuring the attenuation and sound speed of dilute monodisperse MB solutions (5000 microbubbles/ml) with median diameter of 5.2 and 9.8 µm using acoustic pressure range of 10–130 kPa. The attenuation of the medium was calculated by numerically solving the radial oscillations of the MB and incorporating it in the attenuation model. Predictions of the model were in good agreement with the experimental results. As the acoustic pressure increased, the attenuation and maximum sound speed of the medium increased from 5 dB/cm to 12 dB/cm and 1500 to ~1530 m/s, respectively.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".