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Record W4320007061 · doi:10.18280/mmep.090620

Similarity Investigation of Thermosolutal Mixed Convection in a Saturated Porous Medium

2022· article· en· W4320007061 on OpenAlexvenueno aff
Mohamed El Haroui, E. Flilihi, Driss Achemlal, Mohammed Sriti

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsSimilarity solutionPorous mediumMechanicsMass transferPermeability (electromagnetism)ConvectionMatrix similarityHeat transferNonlinear systemPartial differential equationMaterials scienceCombined forced and natural convectionThermodynamicsFluid dynamicsSimilarity (geometry)PorosityNatural convectionBoundary layerChemistryPhysicsMathematicsMathematical analysisComputer scienceComposite material

Abstract

fetched live from OpenAlex

This contribution investigates the thermosolutal convection phenomenon around a thin wall, vertically immersed in a fluid saturating a porous medium of non-uniform permeability, taking into account the thermal conditions of the wall which is exposed to a fluid suction/injection. The conservation equations with boundary conditions have been transformed by the similarity method into a set of nonlinear differential equations. The resulting equations are numerically resolved using a fifth-order Runge-Kutta scheme coupled with the shooting technique. A graphical and physical interpretation of the found results as a function of the control parameters was performed. It is noticed that the heat transfer rate and the mass transfer rate at wall, are intensified for free convection and for significant permeability.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.279
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.018
GPT teacher head0.178
Teacher spread0.160 · 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 teacher head, 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

Citations1
Published2022
Admission routes1
Has abstractyes

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