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Record W2140981503 · doi:10.1002/cjce.22333

A simple heat transfer model for laminar film condensation of superheated vapours on a vertical plate

2015· article· en· W2140981503 on OpenAlexvenueno aff
Zhixiang Zhao, Yanzhong Li, Kang Zhu, Yuan Ma

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsVapoursThermodynamicsCondensationNusselt numberSuperheated steamSuperheatingHeat transferHeat transfer coefficientQuartic functionMaterials scienceChemistryLaminar flowMechanicsPhysicsMathematicsTurbulence

Abstract

fetched live from OpenAlex

Abstract A mathematical model is developed for the study of free convection film condensation for superheated vapours on a vertical plate. The local film thickness as well as the local heat transfer coefficient (HTC) can be obtained through analytically solving the model. The analytical expression shows that local film thickness is proportional to x 1/4 , i.e . δ x = cx 1/4 , where c is the only positive solution of a quartic equation, and the expression is similar to the expression of Nusselt's model. The evaluation of thermophysical properties in the film is improved, which could enhance prediction accuracy. Furthermore, the model is validated by Shang and Wang's model, which strictly solved the two‐phase boundary equations of vapour and liquid film with consideration of various factors. It is obvious that the proposed model is precise for the prediction of superheated vapour film condensation and convenient for use. In addition, the characteristics of film condensation for water vapour as well as other vapours such as R134a, methane (CH 4 ), nitrogen (N 2 ), and hydrogen (H 2 ) are extendedly studied and compared. The results show that variations of heat transfer increase coefficients (HTICs) with subcooling for various vapours have similar trends, but the HTICs are different, e.g. the HTIC for H 2 is 34 times greater than that for water vapour.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.392

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 head0.029
GPT teacher head0.217
Teacher spread0.187 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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