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Thermo-Solutal Convection in Water Isopropanol Mixtures in the Presence of Soret Effect

2010· article· en· W2157022540 on OpenAlexaff
M. Ziad Saghir, Mohammad Azizur Rahman

Bibliographic record

VenueInternational Journal of Fluid Mechanics Research · 2010
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsConvectionMaterials scienceThermophoresisLayer (electronics)Porous mediumFlow (mathematics)ThermodynamicsMechanicsPorosityHeat transferPhysicsComposite material

Abstract

fetched live from OpenAlex

In the present study, the onset of thermo-solutal convection in a liquid layer overlaying a porous layer where the system is being laterally heated is investigated. The non-linear two-dimensional Navier-Stokes equations, the energy equation, the mass balance equation and the continuity equation are solved for the liquid layer and the Brinkman model is used for the porous layer. The partial differential equations are solved numerically using the finite element technique. Two different cases are analyzed in this study. In the case of the thermo-solutal convection without thermodiffusion or Soret effect, multi-convective cells appear in the liquid layer and as the thickness of the liquid layer decreases (i. e. higher thickness ratio), the flow covers the entire cavity. In the presence of Soret effect, it has been found that the isopropanol component goes either towards the hot or cold walls depending on the Soret sign.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.309
Teacher spread0.291 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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