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Record W2007763258 · doi:10.1139/p09-081

Numerical solution of peristaltic transport of an Oldroyd 8-constant fluid in a circular cylindrical tube

2009· article· en· W2007763258 on OpenAlexvenueno aff
Nasir Ali, Yongqi Wang, Tasawar Hayat, Martin Oberlack

Bibliographic record

VenueCanadian Journal of Physics · 2009
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsMechanicsPhysicsNewtonian fluidShear thinningReynolds numberDilatantGeneralized Newtonian fluidPeristalsisShear flowHerschel–Bulkley fluidShear (geology)Fluid dynamicsNon-Newtonian fluidClassical mechanicsTurbulenceShear rateThermodynamicsRheologyMaterials scienceChemistryComposite material

Abstract

fetched live from OpenAlex

The present paper is concerned with the peristaltic flow of a non-Newtonian fluid in circular cylindrical tube. Long wavelength and low Reynolds number approximations are adopted in the problem definition. The non-Newtonian behaviour of the fluid is characterized by the constitutive equation of an Oldroyd 8-constant fluid. The governing nonlinear equation and boundary conditions are solved numerically by a suitable finite-difference method with an iterative scheme. It is seen that shear-thinning and shear-thickening phenomena can be explained through the chosen fluid model. The interaction of shear-thinning and shear-thickening effects with peristaltic motion is studied in detail with particular focus on the basic features of peristalsis such as flow characteristics, pumping characteristics, and trapping. It is found that pressure rise per wavelength against which peristalsis has to work as a positive displacement pump decreases in going from shear-thickening to shear-thinning fluids. Moreover, for strong shear-thinning fluids trapping does not appear. However, a trapped bolus occurs for a weak shear-thinning fluid and its size increases as the fluid is changing from shear thinning towards weak shear thickening. For strong shear-thickening fluids such increase in the size and circulation of bolus stops.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.474

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 head0.197
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

Citations8
Published2009
Admission routes1
Has abstractyes

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