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Record W7066164371

Étude numérique et analytique du transfert thermique par convection naturelle dans des couches poreuses

2016· article· fr· W7066164371 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2016
Typearticle
Languagefr
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
Fundersnot available
KeywordsNatural convectionHeat transferHeat flowConvectionHopf bifurcation
DOInot available

Abstract

fetched live from OpenAlex

Dans ce travail, les études numériques et analytiques ont été réalisés pour évaluer l’effet de la trainée de forme Darcy-Dupuit convection dans une cavité poreuse horizontale rectangulaire saturée par un fluide, soumise à un gradient thermique vertical. L’effet de la trainée de forme sur le seuil de bifurcation Hopf (caractérisant le point de transition entre la solution permanente et oscillante de la convection) a été aussi étudié. Pour une cavité carrée l’analyse de transition d’écoulement est réalisée en considérèrent les flux convectifs mon-cellules ou multi-cellules. Les paramètres régissant ce phénomène sont le nombre de Rayleigh, RT, le rapport de forme, A, et le coefficient de la trainée de forme caractérisée par le nombre de Prandtl modifié, * r P . Pour une couche poreuse élancée (A>>1), on a utilisé l’hypothèse de l’écoulement parallèle afin d’obtenir une solution analytique dans les deux cas (milieu poreux Darcy, milieu poreux Dupuit-Darcy. Les méthodes numériques (ADI et SOR) basées sur la méthode des différences fines sont employées pour obtenir des solutions numériques des équations gouvernantes générales.

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)0.002
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.226
Teacher spread0.213 · 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
Published2016
Admission routes1
Has abstractyes

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