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Record W4386936011 · doi:10.1063/5.0165627

Blockage ratio and Reynolds number effects on flows around a rectangular prism

2023· article· en· W4386936011 on OpenAlexafffund
Fati Bio Abdul-Salam, Xingjun Fang, Mark F. Tachie

Bibliographic record

VenuePhysics of Fluids · 2023
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPhysicsWakeReynolds numberParticle image velocimetryPrismMechanicsVortexVortex sheddingFlow (mathematics)OpticsTurbulenceWater tunnel

Abstract

fetched live from OpenAlex

The combined effects of blockage ratio (BR) and Reynolds number (Re) on the spatiotemporal characteristics of turbulent flow separation around a rectangular prism with depth-to-thickness ratio of 3 were investigated using a time-resolved particle image velocimetry. Four different blockage ratios (BR = 2.5%, 5%, 10%, and 15%) were examined at Reynolds numbers of 3000, 7500, and 15000. Two regimes (unattached and reattached) were identified; however, the boundary between these regimes shows a complex dependency on BR and Re. The mean flow does not reattach onto the prism at low BR and Re but tends to reattach when BR and Re increase. The wake vortices are relatively larger for the unattached test cases. The separation bubbles over and in the wake of the prism are dynamically coupled for prisms in the unattached regime but independent of each other in the reattached regime. Spectral analyses of the velocity fluctuations and coefficient of the first proper orthogonal decomposition mode pair reveal a single dominant peak at the same fundamental shedding frequency for the reattached test cases, whereas multiple competing frequencies are observed for test cases in the unattached regime. The Kelvin–Helmholtz frequency increases with an increase in BR and Re. The vortical structures are more organized for prisms in the reattached regime, and their convective velocities in the wake are comparatively higher.

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 score0.902
Threshold uncertainty score0.526

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 head0.220
Teacher spread0.214 · 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

Citations12
Published2023
Admission routes2
Has abstractyes

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