MétaCan
Menu
Back to cohort
Record W4411092176 · doi:10.1063/5.0270670

Approach flow effects on the wake of a circular cylinder near a bed

2025· article· en· W4411092176 on OpenAlexafffund
Sabal Bista, Chrispin Ebenezer Fredrick-Smiles, G. Nasif, Ram Balachandar

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsWakeMechanicsCylinderFlow (mathematics)Flow visualizationClassical mechanicsGeometry

Abstract

fetched live from OpenAlex

This study numerically investigates the effect of the approaching boundary layer on flow past a circular cylinder positioned at varying distances from the bed. Two turbulent boundary layers with different thickness (thin and thick) were prescribed at the inlet boundary. The cylinder was positioned such that the gap formed between it and the bed varied from 25% to 100% of the diameter. It was noted that a reduction in the gap ratio led to increased asymmetry in the wake region, caused by the deflection of the flow exiting the gap. The change in the approaching boundary layer from thin to thick resulted in a lesser deflection of the gap flow and a smaller recirculation region along the bed. Depending on the gap ratio and the type of the approaching boundary layer, the interaction among the separated shear layers emanating from the cylinder and the bed was found to be different. At a gap ratio of 50%, with the thin boundary layer, more complex vorticity dynamics were observed, including vortex pairing between the vortices emanating from the upper cylinder side and from the bed. The analysis of the spatial two-point correlation of the velocity fluctuations revealed a significant disruption in the coherence of the structures as the gap ratio decreased. For the thick boundary layer cases, the influence of the cylinder wake was more pronounced on the downstream flow near the bed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.633
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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 teacher head, 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

Citations5
Published2025
Admission routes2
Has abstractyes

Explore more

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