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Record W2031522811 · doi:10.1115/ht2005-72744

Effect of Gap Distance on Confined Boiling Heat Transfer Over a Saturated Porous Structure

2005· article· en· W2031522811 on OpenAlexaff
Michael J. Schertzer, M. Khammar, D. Ewing, C.Y. Ching, J.S. Chang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceHeat transferPorous mediumBoilingCapillary actionComposite materialThermocouplePorosityPenetration (warfare)CopperThermodynamicsMetallurgy

Abstract

fetched live from OpenAlex

An experimental investigation was performed to study the effect that the introduction of a gap between a heated fin and a porous media would have on the heat removal characteristics of a capillary evaporator. In these experiments, a thin stainless steel resistive foil stretched between two copper electrodes was used to heat a saturated porous plate with an effective pore size of 50 microns. The temperature distribution on a 10 mm wide simulated fin was measured by a high-speed infra-red thermal imaging system. The heat removal performance was investigated for gap distances of 0.00 to 1.00 mm and for heat fluxes of 17 to 180 kW/m2. These results showed that the maximum heat transfer rate that could be achieved before persistent hot spots were observed on the surface increased with gap distance. Local temperature measurements made using thermocouples embedded in the porous media indicate that vapour penetration into the porous wick is intermittent, and that there is no stable single phase blanket of vapour. For a gap distance of 0.00 mm, this penetration is more uniformly distributed across the width of the heated fin than at a gap distance of 0.50 mm. In the latter case, the vapour distribution is much higher near the edge of the heated fin.

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 score0.139
Threshold uncertainty score0.656

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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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