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Record W4414993904 · doi:10.1063/5.0296909

On the horseshoe vortex characteristics of bed-mounted inclined cylinders

2025· article· en· W4414993904 on OpenAlexafffund
Tapas Kumar Pradhan, Sabal Bista, 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
KeywordsVortexBackflowParticle image velocimetryReynolds numberCylinderFlow (mathematics)VorticityVector field

Abstract

fetched live from OpenAlex

This experimental study investigates the influence of inclination of bed-mounted cylinders on the horseshoe vortex (HSV) generated around them. To this end, the flow past vertical (VC), backward-inclined (BIC), forward-inclined (FIC), and side-inclined (SIC) cylinders were studied using the same fully developed approach flow. Velocity fields upstream of the cylinder-bed junction were measured using particle image velocimetry at a Reynolds number based on cylinder diameter of 26 000. Mean flow analysis revealed well-defined HSV structures in the VC, BIC, and SIC configurations, whereas no distinct HSV was observed for the FIC case. Instantaneous flow field analysis showed that the weakest downflow along the cylinder surface occurred in BIC due to the formation of a vortex above the primary HSV, which trapped and suppressed the downward flow. In contrast, the FIC configuration exhibited the strongest downflow, as its forward inclination provided a more streamlined path to the descending flow. Swirling strength analysis indicated that the strength of the HSV was maximum in BIC, followed by SIC, VC, and FIC. Probability density functions (PDFs) and joint PDFs of velocity fluctuations identified three dominant flow conditions: zero-flow, backflow, and intermediate flow in VC, BIC, and SIC, while FIC exhibited only zero-flow and backflow conditions. Joint PDFs, two-point correlation, and proper orthogonal decomposition analyses further supported the presence of localized, oscillatory HSV structures.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.353

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 head0.238
Teacher spread0.230 · 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

Citations6
Published2025
Admission routes2
Has abstractyes

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