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Record W4404497373 · doi:10.1063/5.0239290

Wake characteristics of near-wall submerged bluff bodies with varying streamwise length

2024· article· en· W4404497373 on OpenAlexafffund
M. Edegbe, G. Nasif, Ram Balachandar

Bibliographic record

VenuePhysics of Fluids · 2024
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsWakeBluffMechanicsClassical mechanics

Abstract

fetched live from OpenAlex

This study aims to investigate the effect of streamwise length on the wake characteristics of submerged sharp-edged bluff bodies in the presence of an underbody gap using large eddy simulation. To this end, three bodies with identical width (W) and height (h), but varying only in their streamwise lengths (L) were employed resulting in streamwise elongation ratios of L/h = 1, 2, and 3, respectively. The underbody gap between the bottom face of the body and the wall was fixed at 0.14 h for all cases. A fully developed turbulent boundary layer with a thickness of 3.6 h was used as the approaching flow. It was noted that the mean flow and turbulent stresses were significantly affected by the streamwise length. Premultiplied frequency spectra of the velocity fluctuations were utilized to examine the fluctuating properties of the wake. A single dominant vortex shedding frequency was observed for L/h = 1 and 3, whereas dual mode vortex shedding was noted for L/h = 2. The latter case exhibited an intermittent reattachment on the top surface of the body. The fluid structures evaluated using the λ2 criterion, indicated that they were strongly influenced by L/h. Interestingly, even with the presence of a gap, a weak horseshoe vortex which occurred intermittently was captured close to the bed for the three cases.

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 score0.832
Threshold uncertainty score0.549

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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

Citations9
Published2024
Admission routes2
Has abstractyes

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