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Record W2345356627 · doi:10.1002/cjce.22525

Bubble growth from first principles

2016· article· en· W2345356627 on OpenAlexafffundvenue
Chaimongkol Saengow, A. Jeffrey Giacomin, Xiànghóng Wú, Chanyut Kolitawong, Chuanchom Aumnate, A. W. Mix

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsQueen's University
FundersNatural Science Foundation of Shandong ProvinceNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsGovernment of Canada
KeywordsBubbleAdiabatic processMechanicsIsothermal processViscosityRADIUSSurface tensionNewtonian fluidViscous liquidPhysicsClassical mechanicsThermodynamicsComputer science

Abstract

fetched live from OpenAlex

We consider the simplest relevant problem in the foaming of molten plastics: the growth of a single bubble in a highly viscous Newtonian fluid without interference from other bubbles. This problem has defied accurate solution from first principles. Classical approaches from first principles have neglected the temperature rise in the surrounding fluid, and we find that this oversimplification greatly accelerates growth prediction. We use transport phenomena to analyze the growth of a solitary bubble, expanding under its own pressure. We consider a bubble of ideal gas growing without the accelerating contribution from mass transfer into the bubble. We find that bubble growth depends upon nucleus radius and nucleus pressure. We begin with a detailed examination of the classical approaches. Our failure to fit data with these approaches sets up the second part of our paper, a novel exploration of the essential decelerating role of viscous heating. We explore both isothermal and adiabatic expansions, and also the decelerating role of surface tension. The adiabatic analysis accounts for the slight deceleration due to the cooling of the expanding gas, which depends on gas polyatomicity. We explore the pressure profile, and the components of the extra stress tensor, in the surrounding fluid. These stresses can be frozen into foamed plastics. We find that our new theory compares well with measured size, when the nucleus radius, nucleus pressure, and melt viscosity are fitted. We include a detailed dimensional worked example to help process engineers with foam design.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

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

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 head0.186
Teacher spread0.171 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2016
Admission routes3
Has abstractyes

Explore more

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