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Record W3109836514 · doi:10.2339/politeknik.768211

A Comparison of Circular Duct and Real Hexagonal Duct Results Using Hydraulic Diameter

2020· article· en· W3109836514 on OpenAlexaff
Umut Barış YILMAZ, Oğuz Turgut

Bibliographic record

VenueJournal of Polytechnic · 2020
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsYukon University
Fundersnot available
KeywordsNusselt numberReynolds numberTurbulencePressure dropDuct (anatomy)Dimensionless quantityHeat transferMechanicsThermodynamicsHydraulic diameterMaterials scienceHeat transfer coefficientPhysicsAnatomyMedicine

Abstract

fetched live from OpenAlex

To see whether the turbulent flow correlations derived for circular ducts can be used for hexagonal cross-sectional ducts using hydraulic diameter, turbulent flow in hexagonal ducts is numerically investigated under constant wall temperature boundary condition using ANSYS Fluent 17.0 software. Investigated parameters are the Reynolds number between 10×103Re50×103 and side angle of the duct varying between 30o and 90o. Standard k-ε model is used as turbulence model. General expressions are proposed for fully developed dimensionless heat transfer coefficient Nusselt number and fully developed Darcy friction factor in terms of Reynolds number and side angle for hexagonal-shaped cross-sectional duct. Results show that side angle of hexagonal duct affects the pressure drop along duct and heat transfer coefficient in duct. Results point out that regular hexagonal duct, =60o, gives minimum pressure drop and maximum Nusselt number. It is concluded that correlations given in the literature for circular ducts in turbulent flow can give 14% higher dimensionless heat transfer coefficient, Nusselt number, than that of actual hexagonal duct flow.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.608

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 head0.057
GPT teacher head0.294
Teacher spread0.237 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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