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Record W3109329526 · doi:10.1080/02286203.2020.1843934

Fractional derivative modeling of double-diffusive free convection with von Neumann stability analysis

2020· article· en· W3109329526 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Modelling and Simulation · 2020
Typearticle
Languageen
FieldMathematics
TopicFractional Differential Equations Solutions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsNusselt numberConvective heat transferSherwood numberThermodynamicsMechanicsFractional calculusHeat transferMomentum (technical analysis)Derivative (finance)ConvectionMaterial derivativeStability (learning theory)MathematicsMathematical analysisPhysicsTurbulenceReynolds number

Abstract

fetched live from OpenAlex

This paper focuses on the problem of fractional time derivative of fluid flow and convective heat and mass transfer from a heated semi-infinite wall immersed. We provided two cases of study, one is free convective heat transfer and the other is a free double-convective heat and mass transfer. The time-derivative terms in the equations of momentum, energy and concentration are assumed to be fractional using the Grunwald-Letnikov (GL) model. A finite difference scheme has been developed for each case of study and followed by a von Neumann stability analysis. Therefore, a stability condition has been derived for each case of study. It was found that the derived stability condition collapses to the traditional one as the derivative order equals one, which reflects an accurate implementation. Also, selected physical results have been presented for the velocity, temperature and concentration profiles as well as variations of Nusselt/Sherwood number and friction coefficient.

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.

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: Empirical · Consensus signal: none
Teacher disagreement score0.527
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 communication0.0000.001
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 head0.147
GPT teacher head0.344
Teacher spread0.197 · 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