MétaCan
Menu
Back to cohort
Record W2041072031 · doi:10.1115/ht2003-47202

Experimental Study on Natural Convection in an Asymmetrically Heated Inclined Channel With Radiation Exchange

2003· article· en· W2041072031 on OpenAlexaff
Qin Lin, S. J. Harrison

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsQueen's University
Fundersnot available
KeywordsNusselt numberHeat fluxEmissivityNatural convectionMechanicsHeat transferMaterials scienceRayleigh numberRayleigh scatteringChannel (broadcasting)Heat transfer coefficientFilm temperatureThermodynamicsGeometryOpticsPhysicsReynolds numberMathematicsTurbulence

Abstract

fetched live from OpenAlex

Heat transfer in an asymmetrically heated, inclined channel by natural convection and radiation exchange was experimentally investigated. Experiments were conducted on channels with small inclination angle (to horizontal) ranging from 18° to 30° and a wall surface emissivity of 0.29 to 0.95. The channel length/space ratio was between 44 and 220. In each test, a uniform heat flux was applied along the top wall of the channel, while the bottom wall was thermally insulated. Temperature profiles along both the top and bottom walls of the channel were recorded under different heat flux and channel length/space ratios. The dependency of maximum wall temperature and heat transfer on the channel spacing and surface emissivity was explored. As a result of this work, correlations of local and average Nusselt number, with modified channel Rayleigh number, were determined and proposed for channels at inclination angle of around 18° and surface emissivities of around 0.95. The proposed correlation will be valid for modified-Rayleigh number in the range of 10 < Ra” < 5.6 × 104 at asymmetric heat flux boundary conditions.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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

Citations4
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicHeat Transfer MechanismsFrench-language works237,207