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Record W3170719585 · doi:10.1115/1.4051428

Mean and Dynamic Aspects of the Wakes of a Surface-Mounted Cube and Block

2021· article· en· W3170719585 on OpenAlexafffund
Bárbara L. da Silva, David S. Sumner, Donald J. Bergstrom

Bibliographic record

VenueJournal of Fluids Engineering · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsWakeVorticityReynolds numberVortex sheddingMechanicsBoundary layerDownwashPhysicsVortexCube (algebra)GeometryTurbulenceOpticsMathematics

Abstract

fetched live from OpenAlex

Abstract The flow downstream of surface-mounted finite height square prisms with aspect ratio AR = 1 (cube) and 0.5 (block) was investigated experimentally in a low-speed wind tunnel, to determine the overall structure and dynamic behavior of the wake and the source of the streamwise vorticity. The Reynolds number based on the prisms' width D was Re =7.5×104 and the boundary layer thickness at the location of the prisms was δ/D=0.73. A vortex shedding frequency was found in the wake of the cube, but no periodicity was found in the wake of the block. The mean wake of the cube showed features of prisms below the critical AR, but the wake of the block had a distinct behavior due to the dominant shear flow from the boundary layer. The shear changed the downwash and, consequently, the streamwise vorticity distribution in the wake, in addition to reducing the magnitude of the Reynolds stresses. The phase-average analysis for the cube revealed the alternate shedding of inclined structures related to the streamwise vorticity in the upper part of the wake. These vorticity regions were caused by the alternate bending and entrainment of the side flow, caused by the downwash. The periodic component of the total Reynolds stresses was, however, significantly smaller than the turbulence-related stresses. This study showed that the wake had a transitional behavior for the cube, but became fundamentally different for the block when compared with prisms of higher AR.

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 score0.002
Threshold uncertainty score0.004

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 head0.004
GPT teacher head0.192
Teacher spread0.188 · 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

Citations17
Published2021
Admission routes2
Has abstractyes

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