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Record W2805838722 · doi:10.1139/cjp-2018-0159

A comparative study on magnetic and non-magnetic particles in nanofluid propagating over a wedge

2018· article· en· W2805838722 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Physics · 2018
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsNanofluidMechanicsHeat transferMagnetic fieldPhysicsMagnetic nanoparticlesLorentz forceConvective heat transferThermodynamicsNanoparticleMaterials scienceCondensed matter physicsClassical mechanicsNanotechnology

Abstract

fetched live from OpenAlex

The purpose of this paper is to investigate convective heat and mass transfer of nanofluid in the context of improving physical properties through magnetic and non-magnetic nanomaterials under the magnetic influence. For this, three magnetic nanoparticles: cast iron, pure iron, and magnetite and three non-magnetic: gold, silver, and copper are taken into account. The physical problem for homogenous nanofluid is modeled by employing the magnetic interaction between nanoparticles through Lorentz force into fundamental equations of thermo-hydrodynamic and correlations models that support effective physical properties. The governing equations in dimensionless form are taken to analyse the nanofluid flow as well as heat profile. The impact of interesting physical parameters like particle volume fraction and magnetic field on patterns of velocity and the temperature are graphically demonstrated and discussed. The effect of concentration and size of nanoparticles on shear stress and heat transfer at the wall are examined through numerical values shown in table form. The results show that the heat transfer rate of a base fluid is enhanced by deploying nanoparticles and further improved by taking small-size magnetic nanoparticles.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.542

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 head0.017
GPT teacher head0.230
Teacher spread0.214 · 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