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Record W1987979939 · doi:10.1115/1.2728905

A Flow Boiling Heat Transfer Investigation of FC-72 in a Microtube Using Liquid Crystal Thermography

2006· article· en· W1987979939 on OpenAlexaff
R. Muwanga, Ibrahim Hassan

Bibliographic record

VenueJournal of Heat Transfer · 2006
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsNucleate boilingHeat fluxMicrochannelMaterials scienceHeat transfer coefficientBoilingHeat transferThermodynamicsCoolantMass fluxMechanicsTube (container)Critical heat fluxComposite materialPhysicsNanotechnology

Abstract

fetched live from OpenAlex

This paper presents experimental measurements of boiling heat transfer in a 1.067 mm inner diameter tube, using liquid crystal thermography for wall temperature measurement. The study was motivated by the two-phase microchannel pumped cooling loop, a recent technology proposed for thermal management of tomorrow's high-end electronics. The working fluid was FC-72, which is a dielectric coolant and measurements were obtained in a closed loop test facility. A unique flow boiling onset was observed whereby a large wall temperature gradient travels along the tube. During flow boiling conditions, wall temperature fluctuations have been observed. The use of a thermographic technique has added insight into the flow boiling characteristics and acts as a partial flow visualization method. Local heat transfer coefficients are presented and compared with correlations for both macro- and microchannels. The heat transfer coefficient is found to be influenced by the heat flux at a lower mass flux but only mildly at a higher mass flux.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.213
Teacher spread0.199 · 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 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

Citations23
Published2006
Admission routes1
Has abstractyes

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