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Record W4402413730 · doi:10.1115/fedsm2024-131252

Characteristics of Turbulent Flow Around Right-Trapezoidal Prisms With Varying Upper and Lower Lengths

2024· article· en· W4402413730 on OpenAlexaff
Aleyna Guney, Fati Bio Abdul-Salam, Amir Sagharichi, Mark F. Tachie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTurbulenceFlow (mathematics)GeologyUpper and lower boundsMechanicsGeometryPhysicsMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract The turbulent characteristics of flow separation induced by trapezoidal prisms subjected to uniform flow are studied using particle image velocimetry (PIV). The streamwise aspect ratios (upper length to lower length) were AR1.0_2.5, AR2.0_2.5, and AR2.0_4.0. The Reynolds number (based on freestream velocity and body height) was Reh = 10000 and the results were analyzed in terms of the mean velocities, Reynolds stresses, and proper orthogonal decomposition. Recirculation bubbles formed in the wake region are asymmetric about the prism centerline, and the lower bubble is smaller than the upper one. Contours of the streamwise Reynolds normal stress exhibit two peaks in the wake of the prisms, and an additional peak over the upper surface of the prism. The peak magnitude of streamwise Reynolds normal stress in the upper and lower wake region are identical. A single peak in the vertical Reynolds normal stress is observed near the centerline of the prism within the wake region. Proper orthogonal decomposition was used to characterize the energetic vortical structures of the flow field around the prisms. The results show that the first two POD modes capture similar relative energy content, regardless of aspect ratio, while the wavelength of the POD decreases as the aspect ratio increases.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.004
GPT teacher head0.183
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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