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Record W3091185750 · doi:10.18280/mmep.070307

A Chebyshev Based Spectral Method for Solving Boundary Layer Flow of a Fractional-Order Oldroyd-B Fluid

2020· article· en· W3091185750 on OpenAlexvenueno aff
Shina Daniel Oloniiju, Sicelo P. Goqo, Precious Sibanda

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChebyshev filterOrder (exchange)Flow (mathematics)MathematicsBoundary layerApplied mathematicsFractional calculusMathematical analysisLayer (electronics)MechanicsPhysicsMaterials scienceComposite material

Abstract

fetched live from OpenAlex

We focused on developing an accurate numerical scheme for the flow of a fractionalorder Oldroyd-B fluid model with the non-isothermal property. In many cases, the direct application of the Chebyshev tau method using the operational matrix of the Chebyshev polynomials usually leads to an accurate solution. However, in some cases, dealing with non-linearity and coupling can be tedious. In this study, we present a numerical method based on Chebyshev polynomials of the first kind and interpolation using Gauss-Lobatto quadrature. The coefficients of the series expansion of the pseudospectral method are obtained through integration of the Chebyshev polynomials orthogonality condition. The numerical results show that the scheme is accurate and reliable. The effects of the fractional-order objective stress rate of the Oldroyd-B fluid on the velocity and shear stress are also presented. The error bound theorems presented in this study support the findings of the numerical computations.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.248
Threshold uncertainty score0.883

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 head0.026
GPT teacher head0.239
Teacher spread0.212 · 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
GenreMethods

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

Citations1
Published2020
Admission routes1
Has abstractyes

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