MétaCan
Menu
Back to cohort
Record W2139987057 · doi:10.1115/1.2130405

Laminar Flow and Heat Transfer in the Entrance Region of Trapezoidal Channels With Constant Wall Temperature

2005· article· en· W2139987057 on OpenAlexaff
Metin Renksizbulut, Hamid Niazmand

Bibliographic record

VenueJournal of Heat Transfer · 2005
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNusselt numberReynolds numberLaminar flowMechanicsHeat transferBoundary layerHagen–Poiseuille equationHydraulic diameterThermodynamicsOpen-channel flowPipe flowFlow (mathematics)PhysicsMaterials scienceTurbulence

Abstract

fetched live from OpenAlex

Abstract Simultaneously developing three-dimensional laminar flow and heat transfer in the entrance region of trapezoidal channels have been investigated using numerical methods in the Reynolds number range from 10 to 1000. The principal and secondary velocity fields, the temperature field, and all associated heat and momentum exchange parameters have been examined. The present results for the fully developed flow region of the channels compare well with the available literature. In the entrance region, it is observed that the axial velocity profiles develop overshoots near the walls and particularly at the channel corners. It is shown that boundary-layer type of approximations, which lead to Reynolds-number-independent Poiseuille and Nusselt numbers, can be used for Reynolds numbers over 50 and after a few hydraulic diameters from the channel inlet. It is also shown that hydrodynamic entrance lengths calculated with methods based on fully developed flow data are grossly in error. New correlations are proposed for the entrance length, and for the friction and heat transfer coefficients.

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 score0.002
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.006
GPT teacher head0.177
Teacher spread0.172 · 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

Citations54
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Heat TransferSame topicFluid Dynamics and Turbulent FlowsFrench-language works237,207