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Record W1986911264 · doi:10.2298/tsci141102148h

Water-based squeezing flow in the presence of carbon nanotubes between two parallel disks

2014· article· en· W1986911264 on OpenAlexaff
Rizwan Ul Haq, Zakia Hammouch, Waqar A. Khan

Bibliographic record

VenueThermal Science · 2014
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCarbon nanotubeNusselt numberFlow (mathematics)Ordinary differential equationMaterials sciencePartial differential equationMagnetohydrodynamicsCarbon fibersMechanicsDifferential equationNanotechnologyComposite materialPhysicsMathematicsMagnetic fieldMathematical analysisReynolds number

Abstract

fetched live from OpenAlex

Present study is dedicated to investigate the water functionalized carbon nanotubes squeezing flow between two parallel discs. Moreover, we have considered magnetohydrodynamics effects normal to the disks. In addition we have considered two kind of carbon nanotubes named: single wall carbon nanotubes (SWCNT) and multiple wall carbon nanotubes (MWCNT) with in the base fluid. Under this squeezing flow mechanism model has been constructed in the form of partial differential equation. Transformed ordinary differential equations are solved numerically with the help of Runge-Kutta-Fehlberg method. Results for velocity and temperature are constructed against all the emerging parameters. Comparison among the SWCNT and MWCNT are drawn for skin friction coefficient and local Nusselt number. Conclusion remarks are drawn under the observation of whole analysis.

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.234
Teacher spread0.218 · 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

Citations40
Published2014
Admission routes1
Has abstractyes

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