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Record W2026792690 · doi:10.1139/cjp-2013-0465

Simultaneous effects of variable viscosity and thermal conductivity on peristaltic flow in a vertical asymmetric channel

2014· article· en· W2026792690 on OpenAlexvenueno aff
Kh. S. Mekheimer, Y. Abd Elmaboud

Bibliographic record

VenueCanadian Journal of Physics · 2014
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsMechanicsThermal conductivityStream functionViscosityNewtonian fluidHeat transferAmplitudeWavelengthFlow (mathematics)ThermodynamicsOptics

Abstract

fetched live from OpenAlex

This paper discusses the effects of variable viscosity and thermal conductivity on peristaltic flow of a Newtonian fluid in a vertical asymmetric channel. Both viscosity and thermal conductivity are considered as a function of temperature. The long wavelength approximation is used to linearize the governing equations. The system of the governing nonlinear partial differential equation is solved using the perturbation method. Solutions are obtained for the velocity field, the temperature and the concentration. Asymmetry in the flow is induced by traveling waves of different phase and amplitude that propagate along the channel walls. The numerical results show that variable viscosity and thermal conductivity have significant influence on velocity, temperature, and mass transfer. The importance of pertinent flow parameters entering into the flow modeling is discussed.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.174
Teacher spread0.169 · 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

Citations67
Published2014
Admission routes1
Has abstractyes

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