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Record W2188228235 · doi:10.1139/tcsme-2010-0021

MHD FLOW AND HEAT TRANSFER OF TWO IMMISCIBLE FLUIDS BETWEEN MOVING PLATES

2010· article· en· W2188228235 on OpenAlexvenueno aff
Živojin Stamenković, Dragiša Nikodijević, Bratislav Blagojević, Slobodan Savić

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetohydrodynamic driveMagnetohydrodynamicsHartmann numberMechanicsHeat transferMagnetic fieldIsothermal processFlow (mathematics)PhysicsFlow velocityMaterials scienceThermodynamics

Abstract

fetched live from OpenAlex

The magnetohydrodynamic (MHD) flow of two immiscible and electrically conducting fluids between isothermal, insulated moving plates in the presence of an applied electric and inclined magnetic field has been investigated in the paper. The partial differential equations governing the flow and heat transfer are solved analytically with appropriate boundary conditions for each fluid and these solutions have been matched at the interface. The numerical results for various values of the Hartmann number, the angle of magnetic field inclination, load parameter and the ratio of electrical and thermal conductivities have been presented graphically. It was found that decrease of magnetic field inclination angle flattens out the velocity and temperature profiles. With the increase of the Hartmann number velocity gradients near the plate’s increases, temperature in the middle of the channel decreases and near the plate’s increases. Induced magnetic field is evidently suppressed with an increase of the Hartman number. The effect of changes of the load factor is to aid or oppose the flow as compared to the short-circuited case.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.566
Threshold uncertainty score0.731

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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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 designBench or experimental
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

Citations27
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicNanofluid Flow and Heat TransferFrench-language works237,207