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Record W3106220297 · doi:10.1088/1402-4896/abc927

Finite difference simulation for oblique stagnation point flow of viscous nanofluid towards a stretching cylinder

2020· article· en· W3106220297 on OpenAlexaff
A. Abbasi, W. Farooq, Fazle Mabood, Zahid Hussain

Bibliographic record

VenuePhysica Scripta · 2020
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsFanshawe College
Fundersnot available
KeywordsNanofluidMechanicsStagnation pointCylinderMaterials scienceCurvatureBoundary value problemFlow (mathematics)Classical mechanicsPhysicsHeat transferGeometryMathematics

Abstract

fetched live from OpenAlex

Abstract This study describes the effects of hydrodynamic, thermal and solutal slips on the flow of viscous nanofluid impinging obliquely on the surface of stretching cylinder. An appropriate coordinate decomposition converts the governing non-linear partial differential equations into system of ordinary differential equations along with boundary conditions. An implicit finite difference scheme is used to approximate the governing system for particular values of the involved parameters. Behaviors of various involved parameters on velocity, temperature and concentration profiles are graphically presented and discussed. The numerical results for both orthogonal and non-orthogonal flow are computed and compared with the existing literature for stretching sheet case as well as for stretching cylinder. It is observed that shear velocity of nanofluid decreases by increasing velocity ratio parameter and increases by increasing curvature of cylinder, also the position of the stagnation point for flat plate and cylinder is rapidly change with increase in slip.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.808
Threshold uncertainty score0.720

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 head0.030
GPT teacher head0.246
Teacher spread0.217 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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