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Record W4406038343 · doi:10.18311/jmmf/2023/47285

Effect of Viscous Dissipation and Thermal Radiation on Thermal Properties of MHD Nanofluid in a Curved Channel

2024· article· en· W4406038343 on OpenAlexaff
C. Kavitha, G. Neeraja, N. Gayathri, Sudhir Patel

Bibliographic record

VenueJournal of Mines Metals and Fuels · 2024
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsNanofluidMagnetohydrodynamicsThermal radiationMechanicsThermalDissipationChannel (broadcasting)Materials scienceRadiationPhysicsHeat transferThermodynamicsOpticsEngineeringPlasmaElectrical engineeringNuclear physics

Abstract

fetched live from OpenAlex

The effects of radiation and magnetohydrodynamics on the peristaltic flow of a nanofluid through a porous media in a two-dimensional circular asymmetric channel have been theoretically analysed in terms of viscous dissipation. Under the assumption of a radially uniform magnetic field, the nanofluid is electrically conducting. The radiation response, thermophoresis, and Brownian motion are all taken into consideration by the transport equation. The assumptions of a long wavelength and a low Reynolds number have further simplified the problem. The impact of many parameters on the flow characteristics has been examined through graphical representations using MATLAB bvp4c. Further, impact of Nusselt and Sherwood numbers are studied and its effects are displayed through graphs. Also impact of Schmidt and Soret numbers are examined.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.010
GPT teacher head0.224
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

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
Published2024
Admission routes1
Has abstractyes

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