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Record W1998486791 · doi:10.1139/p08-115

Dissipation of intense vortices

2009· article· en· W1998486791 on OpenAlexvenueno aff
Yasser Aboelkassem

Bibliographic record

VenueCanadian Journal of Physics · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsnot available
Fundersnot available
KeywordsVortexPhysicsDissipative systemDissipationTransformation (genetics)Classical mechanicsVorticityMatrix similarityBurgers vortexMechanicsPartial differential equationQuantum mechanics

Abstract

fetched live from OpenAlex

In this article, we extend the space-time analogy shared by viscous vortices to generalize the dissipation of intense vortices Vatistas and Aboelkassem (Am. Inst. Aeronaut. Astronaut. J. 44, 912 (2006)). The main objective is to layout a mathematical algorithm that can be used to transform vortices into their dissipative phase or into a steady-state counterpart via a similarity transformation to Navier–Stokes equations. The method is applied to examine the time decay of eddies that belong to the Oseen-like concentrated type of viscous vortices. The steady-state Burgers’ vortex model was used to validate the transformation approach. This analysis shows that, upon variable transformation, Burgers’ vortex model has changed into the Oseen–Lamb class of decaying vortices. The approach is simple, general, and applicable to all kinds of viscous incompressible vortices like those of Sullivan, Rott, Bellamy-Knights, Vatistas, and Scully.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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