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Record W3170732303 · doi:10.3390/en14123579

The Steady Wake of a Wall-Mounted Rectangular Prism with a Large-Depth-Ratio at Low Reynolds Numbers

2021· article· en· W3170732303 on OpenAlexafffund
Arash Zargar, Ali Tarokh, Arman Hemmati

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsLakehead UniversityUniversity of Alberta
FundersCanada First Research Excellence Fund
KeywordsWakeReynolds numberDownwashMechanicsPrismDragVorticityGeometryLift-to-drag ratioLift (data mining)PhysicsOpticsVortex sheddingAspect ratio (aeronautics)Drag coefficientVortexMathematicsTurbulence

Abstract

fetched live from OpenAlex

The wakes of wall-mounted small (square) and large (long) depth-ratio rectangular prisms are numerically studied at Reynolds numbers of 50–250. The large depth-ratio significantly alters the dominance of lateral secondary flow (upwash and downwash) in the wake due to the reattachment of leading-edge separated flow on the surfaces of the prism. This changes the wake topology by varying the entrained flow in the wake region and changing the distribution of vorticity. Thus, the magnitude of vorticity significantly decreases by increasing the prism depth-ratio. Furthermore, the length of the recirculation region and the orientation of near wake flow structures are altered for the larger depth-ratio prism compared to the square prism. Drag and lift coefficients are also affected due to the change of pressure distributions on the rear face of the prism and surface friction force. This behavior is consistently observed for the entire range of Reynolds numbers considered here. The wake size is scaled with Re1/2, whereas drag coefficient scaled with Re−0.3.

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: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.349

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 head0.003
GPT teacher head0.197
Teacher spread0.194 · 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

Citations8
Published2021
Admission routes2
Has abstractyes

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