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Record W1603570946 · doi:10.1115/imece2014-37053

Dynamics of a Micro-Bubble Between Two Spherical Particles

2014· article· en· W1603570946 on OpenAlexafffund
Mainul Hasan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicUltrasound and Cavitation Phenomena
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBubbleMechanicsCompressibilityPhysicsParametric statisticsBoundary (topology)Boundary value problemBoundary element methodClassical mechanicsTracking (education)Finite element methodMathematicsMathematical analysisThermodynamics

Abstract

fetched live from OpenAlex

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.

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)0.000
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.250
Teacher spread0.238 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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