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Record W2078067888 · doi:10.1088/0169-5983/42/5/055507

Density maximum effect on Soret-induced natural convection in a square porous cavity

2010· article· en· W2078067888 on OpenAlexaff
Z. Alloui, L. Robillard, P. Vasseur

Bibliographic record

VenueFluid Dynamics Research · 2010
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsUniversité de MontréalPolytechnique Montréal
Fundersnot available
KeywordsNusselt numberStreamlines, streaklines, and pathlinesNatural convectionRayleigh numberLewis numberMechanicsThermodynamicsDimensionless quantityCombined forced and natural convectionMaterials scienceFinite volume methodConvectionPhysicsMathematicsReynolds numberMass transferTurbulence

Abstract

fetched live from OpenAlex

This paper reports a numerical study on the effect of density maximum on Soret-induced convection in a square porous cavity. Dirichlet boundary conditions for temperature are applied to the vertical walls of the enclosure, while the two horizontal ones are assumed impermeable and insulated. The non-dimensional equations for momentum, energy and concentration are solved by a finite volume method with power-law scheme for convection and diffusion. A parametric study is undertaken as a function of the main dimensionless group characterizing the problem, namely the thermal Rayleigh number, RT, the solutal Rayleigh number, RS, the Lewis number Le and an extremum parameter γ, which quantifies the effect of the nonlinear equation of state. The results are presented in the form of streamlines, isotherms and isoconcentration lines for various values of the governing parameters. Comprehensive Nusselt number data are presented as functions of the governing parameters mentioned above.

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 score0.002

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)0.0010.000

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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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

Citations5
Published2010
Admission routes1
Has abstractyes

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