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A CONJUGATE MODEL FOR BUBBLE GROWTH IN LOW-VELOCITY SUBCOOLED FLOWS

2020· article· en· W3048839041 on OpenAlexaff
Maryam Medghalchi, Nasser Ashgriz

Bibliographic record

VenueHeat Transfer Research · 2020
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBubbleSubcoolingMechanicsMaterials scienceEvaporationCondensationThermodynamicsThermal conductionBoundary layerHeat transferPhysics

Abstract

fetched live from OpenAlex

A model for the growth of a bubble on a horizontal heated surface with a constant temperature and in a subcooled condition is presented. The model considers microlayer evaporation, transient thermal boundary layer conduction, and surface condensation or evaporation. The bubble growth time is divided into several stages, and the equation describing the bubble growth is simplified for different stages using a new characteristic time, and a new characteristic size. Several analytical solutions for the bubble growth are obtained at the early stages of the bubble growth and before the bubble lifts off. It is shown that before a critical time, the bubble growth is mainly governed by microlayer evaporation, however after the critical time the bubble growth is controlled by surface evaporation.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.107
GPT teacher head0.321
Teacher spread0.215 · 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 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
Published2020
Admission routes1
Has abstractyes

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