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A Comparative Study of Heat Transfer Coefficients for Film Condensation

2012· article· en· W1745135264 on OpenAlexvenueno aff
Xiaoyong Wei, Xiande Fang, Rongrong Shi

Bibliographic record

VenueEnergy science and technology · 2012
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCondensationHeat transferFlow (mathematics)Materials scienceMechanicsHeat transfer coefficientThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Film condensation heat transfer has wide applications in a variety of industrial systems. A number of film condensation heat transfer correlations (FCHTCs) have been proposed. However, their predictions are often inconsistent. This paper presents a comparative study of existing FCHTCs. Totally 1214 experimental data points are obtained from 10 published papers, and 14 FCHTCs are reviewed, among which four correlations are used for horizontal flow outside smooth tubes, three for flow on vertical surfaces of plates or tubes, two for flow inside smooth tubes either vertically or horizontally, and five for horizontal flow inside smooth tubes. 13 FCHTCs are compared with the experimental data. There are three FCHTCs for horizontal flow inside smooth tubes having a mean absolute relative deviation (MARD) less than 26%, among which the best one has an MARD of 22.2%. More efforts should be made to develop better correlations. Key words: Correlation; Heat transfer; Film; Condensation

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)0.002
metaresearch head score (Gemma)0.008
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.266
Teacher spread0.243 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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