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A Comparative Study of Heat Transfer Coefficients for Film Condensation

2012· article· en· W1745135264 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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 score0.236
Threshold uncertainty score0.211

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 head0.022
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