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Record W2305011830 · doi:10.1139/cjp-2015-0511

Numerical analysis of Walters-B fluid flow and heat transfer over a stretching cylinder

2016· article· en· W2305011830 on OpenAlexvenueno aff
Abid Majeed, Tariq Javed, Sumyya Shami

Bibliographic record

VenueCanadian Journal of Physics · 2016
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHeat transferMechanicsStreamlines, streaklines, and pathlinesCylinderPotential flow around a circular cylinderStagnation pointParasitic dragDragBoundary layerCurvatureWeissenberg numberClassical mechanicsDimensionless quantityFlow (mathematics)ThermodynamicsGeometryOpen-channel flowMathematics

Abstract

fetched live from OpenAlex

Two-dimensional hydromagnetic flow and heat transfer of Walters-B fluid towards a stagnation point region over a stretching cylinder is discussed. Constitutive equations are transformed into dimensionless form by means of suitable similarity transformations. Spectral quasi-linearization method is employed to obtain the solution of similarity equations. Comparison of computed results with existing results in the limiting case of a flat sheet is also provided. Analysis of obtained results is performed through graphs to discuss the influence of emerging parameters on the velocity and temperature profiles. The flow and heat transfer characteristics are analyzed through parameters representing curvature of cylinder, velocity ratio parameter, magnetic parameter, and Weissenberg number. The curvature of the cylinder has significant impact on the velocity and temperature. A magnetic field applied externally suppresses the bulk motion and alters the momentum boundary layer thickness. The drag and heat transfer rate on the surface of the cylinder are examined through skin friction and heat transfer coefficients. Furthermore, streamlines are drawn to see the flow pattern.

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: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.385

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 head0.009
GPT teacher head0.199
Teacher spread0.190 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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