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Record W4206258092 · doi:10.1016/j.dib.2022.107819

Flow visualization data from experiments with an oscillating circular cylinder in a gravity-driven soap film

2022· article· en· W4206258092 on OpenAlexaff
Emad Masroor, Wenchao Yang, Mark A. Stremler

Bibliographic record

VenueData in Brief · 2022
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsQueen's University
FundersNational Science Foundation
KeywordsWakeCylinderFlow visualizationReynolds numberKármán vortex streetSoap filmDimensionless quantityOscillation (cell signaling)MechanicsPhysicsVortexVortex sheddingFlow (mathematics)Transverse planeOpticsGeometryTurbulenceMathematicsEngineering

Abstract

fetched live from OpenAlex

This article contains flow visualization data from experiments conducted in an inclined gravity-driven soap film intersected by a circular cylinder undergoing controlled transverse oscillations at a Reynolds number of Re≈235. The dimensionless frequency and amplitude of cylinder oscillation were varied systematically over the ranges 0.2<f*<1.8 and 0.1<A*<1.3. A high-speed camera was used to capture the interference fringe patterns reflected from the soap film. These videos show the structure of the wake behind the cylinder, including the initial formation of vortices and the extended ‘vortex street’. Several wake patterns were identified, including the classic 2S, P+S, 2P, and 2T patterns, which are discussed in detail in the accompanying research article titled “The wake of a transversely oscillating circular cylinder in a flowing soap film at low Reynolds number” [1]. The videos presented in this article can be accessed through the Virginia Tech University Libraries’ Repository at https://doi.org/10.7294/14448027.v5 [2].

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.294
Teacher spread0.250 · 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 designBench or experimental
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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