MétaCan
Menu
Back to cohort
Record W2896180334 · doi:10.1063/1.5046090

Proper orthogonal decomposition analysis of a circular cylinder undergoing vortex-induced vibrations

2018· article· en· W2896180334 on OpenAlexafffund
Graham Riches, Robert J. Martinuzzi, Chris Morton

Bibliographic record

VenuePhysics of Fluids · 2018
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPhysicsWakeVortex sheddingReynolds numberCylinderPoint of deliveryMechanicsVortexOscillation (cell signaling)VibrationProper orthogonal decompositionFlow (mathematics)Classical mechanicsGeometryTurbulenceAcousticsMathematics

Abstract

fetched live from OpenAlex

Proper orthogonal decomposition (POD) is utilized to analyze the wake-dynamics of a low-mass ratio circular cylinder undergoing vortex-induced vibrations in the initial and upper branches (U* = U∞/fND = 4.07, 5.32). POD allows for characterizing dynamics at frequencies which differ from the cylinder oscillation that cannot be captured with conventional phase-averaging. POD modes contributing to the dominant coherent motions are described in detail. Fourier analysis techniques are used to identify relationships between the POD modes describing non-periodic dynamics linked to the slow-varying base flow and result in a modulation in the strength of vortex shedding. Heuristic models based on mean-field theory are proposed for the POD temporal coefficients. The modelled wake dynamics are found to account for a significant contribution to the Reynolds stresses. In the initial branch, it is found that 6 POD modes are required to capture the salient aspects of the flow, while in the upper branch, 7 modes are required.

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)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.258
Teacher spread0.243 · 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

Citations105
Published2018
Admission routes2
Has abstractyes

Explore more

Same venuePhysics of FluidsSame topicFluid Dynamics and Vibration AnalysisFrench-language works237,207