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Record W4404997209 · doi:10.1063/5.0242481

Modeling time-delayed acoustic interactions of cavitation bubbles and bubble clusters

2024· article· en· W4404997209 on OpenAlexafffund
Pierre Coulombel, Fabian Denner

Bibliographic record

VenuePhysics of Fluids · 2024
Typearticle
Languageen
FieldMaterials Science
TopicUltrasound and Cavitation Phenomena
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBubbleCavitationPhysicsCompressibilityMach numberMechanicsSound pressureAcousticsAcoustic waveAmbient pressureSpeed of soundResonance (particle physics)SonochemistryClassical mechanicsThermodynamicsAtomic physics

Abstract

fetched live from OpenAlex

We propose a low-dimensional modeling approach to simulate the dynamics, acoustic emissions, and interactions of cavitation bubbles, based on a quasi-acoustic assumption. This quasi-acoustic assumption accounts for the compressibility of the medium surrounding the bubble and its finite speed of sound, whereby the potential of the acoustic wave emitted by the bubble propagates along outgoing characteristics. With these ingredients, a consistent set of equations describing the radial bubble dynamics as well as the resulting acoustic emissions and bubble–bubble interactions is obtained, which is accurate to the first order of the Mach number. This model is tested by considering several representative test cases, including the resonance behavior of multiple interacting bubbles and the response of dense mono- and polydisperse bubble clusters to a change in ambient pressure. The results are shown to be in excellent agreement with results reported in the literature. The differences associated with the finite propagation speed of the acoustic waves are observed to be most pronounced for the pressure-driven bubble dynamics in dense bubble clusters and the onset of cavitation in response to a change in ambient pressure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.264
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2024
Admission routes2
Has abstractyes

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