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Record W2594050140 · doi:10.1139/cjp-2016-0853

Parameters identification for the unsteady helical flows of a generalized Oldroyd-B fluid model based on its numerical solution

2017· article· en· W2594050140 on OpenAlexvenueno aff
Ying Ma, Xiaoyun Jiang, Bo Yu

Bibliographic record

VenueCanadian Journal of Physics · 2017
Typearticle
Languageen
FieldMathematics
TopicFractional Differential Equations Solutions
Canadian institutionsnot available
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsPhysicsApplied mathematicsNewtonian fluidInversion (geology)Relaxation (psychology)Mathematical analysisMechanicsMathematics

Abstract

fetched live from OpenAlex

In this paper, we mainly consider the problem of parameter identification for the unsteady helical flows of a generalized Oldroyd-B fluid between two infinitely long coaxial circular cylinders. The implicit finite difference method is employed to obtain the numerical solution for the direct problem. By means of the Levenberg–Marquardt method, the numerical inversion for identifying the three parameters of the model is implemented simultaneously, that is, the Riemann–Liouville time-fractional derivative α, relaxation time λ, and retardation time λr. To test the validity of the proposed numerical method, varied initial guesses and the observed data, whether or not they involve random error, have been used to verify the reliability of the estimation. This paper provides an efficient method to obtain the estimated value of the unknown parameters for the generalized non-Newtonian fluids model.

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)0.001
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.157
GPT teacher head0.346
Teacher spread0.190 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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