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Record W2095330842 · doi:10.2298/tsci0701017h

Numerical investigation of fluid flow and heat transfer characteristics in sine, triangular, and arc-shaped channels

2007· article· en· W2095330842 on OpenAlexaff
Z. Hossain, Sadrul Islam

Bibliographic record

VenueThermal Science · 2007
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsWestern University
FundersBangladesh University of Engineering and Technology
KeywordsReynolds numberMechanicsHeat transferFlow (mathematics)PhysicsHele-Shaw flowOpen-channel flowArc (geometry)Classical mechanicsMaterials scienceGeometryMathematicsTurbulence

Abstract

fetched live from OpenAlex

Time dependent Navier-Stokes and energy equations have been solved to investigate the fluid flow and heat transfer characteristics in wavy channels. Three different types of two dimensional wavy geometries (e.g. sine-shaped, triangular, and arc-shaped) are considered. All of them are of single wave and have same geometric dimensions. Periodic boundary conditions are used to attain fully developed flow. The flow in the channels has been observed to be steady up to a critical Reynolds number, which depends on the geometric configuration. Beyond the critical Reynolds number a self-sustained oscillatory flow has been observed. As a result of this oscillation, there is increased mixing between core and the near-wall fluids, thereby increasing the heat transfer rate. For the same geometric dimensions, flow becomes unsteady at relatively lower Reynolds number in the arc-shaped channel. .

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.012
GPT teacher head0.215
Teacher spread0.203 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

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