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Cylinder Wake Dynamics in the Presence of Stream-Wise Harmonic Forcing

2006· article· en· W2127913212 on OpenAlexaff
Mathieu Rodriguez, Njuki Mureithi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsWakePhysicsVortexMechanicsDragKármán vortex streetLift (data mining)CylinderClassical mechanicsWake turbulenceAmplitudeVortex sheddingTurbulenceGeometryOpticsReynolds numberMathematics

Abstract

fetched live from OpenAlex

The vortex wake flow dynamics downstream of a cylinder undergoing streamwise harmonic (fe/fs=1) forced oscillations has been investigated numerically using a CFD code for Re=1000. The steady-state of the wake flow has been analysed considering the amplitude of oscillations as a perturbation parameter. The resulting dynamics of the fluid lift and drag forces acting on the cylinder have been linked to the different vortex wake modes observed downstream of the cylinder. Forced oscillations lead to periodic, quasi-periodic and chaotic responses depending on the amplitude of oscillation of the cylinder. Different vortex wake patterns or modes (including 2S, P+S and S modes) have also been identified and described. Symmetry related bifurcations both in the computed fluid force dynamics as well as in the vortex wake patterns were identified. The key role played by spatio-temporal symmetry in the interaction between the wake flow and the oscillating cylinder has been elucidated by a Proper Orthogonal Decomposition (POD) of the wake velocity field. Symmetric and antisymmetric spatio-temporal modes were identified and bifurcations in the wake flow were explained in terms of mode interactions in the wake.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.404

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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
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

Citations5
Published2006
Admission routes1
Has abstractyes

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