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Record W7116122908 · doi:10.82417/v3xz-pd31

Effect of partial sheltering on spanwise wake interference of unequal-height tandem circular cylinders

2025· other· en· W7116122908 on OpenAlexfundno aff

Bibliographic record

VenueEspace ÉTS (ETS) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWakeParticle image velocimetryVortex sheddingReynolds numberVortexCylinderEntrainment (biomusicology)Boundary layerWake turbulenceFlow (mathematics)

Abstract

fetched live from OpenAlex

Time-resolved particle image velocimetry is used to investigate the effects of partial sheltering on the unsteady wake dynamics of unequal-height tandem cylinders submerged in a turbulent boundary layer (TBL). The height ratio of the cylinders was kept constant at ℎ/▯ = 0.75 based on the aspect ratios of ℎ/▯ = 5.3 for the upstream (UC) and ▯/▯ = 7.0 for the downstream (DC) cylinders, where ℎ and ▯ represent the height of the UC and DC, respectively and ▯ the diameter of the cylinders. The center-to-center spacing between the cylinders was 4▯, Reynolds number based on the cylinder diameter (▯) was 5540 and the submergence ratio was ▯/▯ = 1.2, where ▯ is the TBL thickness. Measurements were performed in three streamwise-spanwise planes along the height of the tandem cylinders (TC) and single cylinder (SC) identical to the DC. The results showed that wake interference by the DC enhanced the near wall reverse flow region, while reducing the vortex shedding frequency behind the UC compared to the SC. For the DC, the enhanced flow entrainment from the side accelerated the vortex formation of larger structures in the sheltered region, while delaying the vortex formation at the unsheltered free end. As a result, the reverse flow region was reduced in the sheltered portion but enhanced near the free end of the DC.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 science0.0000.001
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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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