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Record W2021523282 · doi:10.1615/ichmt.2008.cht.180

ENTROPY PRODUCTION FOR DEVELOPING LAMINAR MIXED CONVECTION IN VERTICAL TUBES

2008· article· en· W2021523282 on OpenAlexaff
Ridha Ben Mansour, Nicolas Galanis, Cong Tam Nguyen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsUniversité de MonctonUniversité de Sherbrooke
Fundersnot available
KeywordsGrashof numberMechanicsEntropy productionLaminar flowHeat transferCombined forced and natural convectionThermodynamicsHeat fluxNatural convectionCompressibilityPhysicsEntropy (arrow of time)Nusselt numberReynolds number

Abstract

fetched live from OpenAlex

The problem of hydro-dynamically and thermally developing laminar mixed convection in a vertical tube with uniform wall heat flux has been studied numerically. The flow was assumed steady and axis-symmetrical and the fluid incompressible with constant thermo-physical properties except for its density in the gravity forces (Boussinesq's assumption). The system of non-linear, elliptic and coupled governing equations, subjected to appropriate boundary conditions, was successfully solved using the finite-control-volume method, a staggered non-uniform 34 (r) x 40 (φ) x 700 (z) grid and the power-law scheme for computing the heat and momentum fluxes. The modified SIMPLE procedure was used to treat the velocity-pressure coupling. Numerical results obtained for the developing velocity and temperature profiles of water were used to compute the rate of entropy production due to heat transfer and viscous effects. Some significant results showing profiles of these variables for various axial positions and different Grashof numbers are presented and discussed. The entropy profiles in the fully developed region are in excellent agreement with the corresponding analytical results. These results clearly show that the entropy production by both mechanisms is more important near the tube wall. In general, the entropy production due to heat transfer is several orders of magnitude larger than that due to viscous effects. It has also been found that the entropy generation increases considerably with an augmentation of the Grashof number.

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 score0.001
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 communication0.0000.000
Open science0.0000.001
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 head0.021
GPT teacher head0.213
Teacher spread0.192 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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