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Record W2910865703 · doi:10.1063/1.5079750

Effect of yaw angle on flow structure and cross-flow force around a circular cylinder

2019· article· en· W2910865703 on OpenAlexafffund
Ran Wang, Shaohong Cheng, David S.‐K. Ting

Bibliographic record

VenuePhysics of Fluids · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStrouhal numberPhysicsLift coefficientMechanicsReynolds numberVortex sheddingLift (data mining)VortexPotential flow around a circular cylinderFlow visualizationCylinderWakeFlow (mathematics)Classical mechanicsGeometryTurbulenceMathematics

Abstract

fetched live from OpenAlex

Flow around an inclined circular cylinder at yaw angles of α = 0°, 30°, 45°, and 60° has been numerically studied using the delayed detached eddy simulation at a Reynolds number of 1.4 × 104. Periodic boundary conditions are utilized to minimize the end effect. The focus is to explore the effect of yaw angle on the flow structure and the spatial distribution of the cross-flow forces. For the normal flow case, the modulation of the span-wise averaged lift force coefficient is found to be related to the unstable shear layer. For the inclined cases, contours of the sectional lift force coefficient show that the local vortex shedding staggers in time along the axial span at the early stage of the simulation, when the flow approaches the cylinder. After the flow reaches the quasi-periodic state, the axial difference disappears for α > 45° but not for α = 30°. In particular, the axial difference of the sectional lift force coefficient results in a near-zero value of the span-wise averaged lift force coefficient. The transition from a two-dimensional flow to a three-dimensional one is not captured in the current simulation. However, wake visualization indicates a mitigation of von Kármán vortex shedding when the yaw angle is greater than 30°. Although the Strouhal number is well predicted by the Independence Principle (IP), other flow properties are less agreeable with the prediction by IP.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.222
Teacher spread0.218 · 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
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

Citations37
Published2019
Admission routes2
Has abstractyes

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