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Record W2034839903 · doi:10.1115/1.2946474

Slip Flow Heat Transfer in Annular Microchannels With Constant Heat Flux

2008· article· en· W2034839903 on OpenAlexafffund
Zhipeng Duan, Yuri S. Muzychka

Bibliographic record

VenueJournal of Heat Transfer · 2008
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKnudsen numberHeat transferMechanicsHeat fluxNusselt numberTemperature jumpLaminar flowSlip ratioThermodynamicsMaterials scienceSlip (aerodynamics)Heat transfer coefficientAdiabatic processReynolds numberPhysicsShear stressTurbulence

Abstract

fetched live from OpenAlex

Microscale fluid dynamics has received intensive interest due to the emergence of microelectromechanical systems technology. When the mean free path of the gas is comparable to the channel’s characteristic dimension, the continuum assumption is no longer valid and velocity slip and temperature jump may occur at the duct walls. Slip flow heat transfer in annular microchannels has been examined. The effects of velocity slip and temperature jump on the hydrodynamically and thermally fully developed heat transfer characteristics for laminar flow have been studied analytically. The analysis is carried out for both uniform wall heat flux on one wall, adiabatic on the other wall, and uniform wall heat flux on both walls. The results indicate that the slip flow Nusselt numbers are lower than those for continuum flow and decrease with an increase in Knudsen number for most practical engineering applications. The effects of Knudsen number, radius ratio, and heat flux ratio on heat transfer characteristics are discussed, respectively.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.020
GPT teacher head0.238
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 source (direct Gemma or distilled Codex), 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

Citations42
Published2008
Admission routes2
Has abstractyes

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