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Record W4404962700 · doi:10.1063/5.0238122

Influence of sweep angle on leading edge vortex dynamics of a fully passive oscillating-plate hydrokinetic turbine prototype

2024· article· en· W4404962700 on OpenAlexafffund
Waltfred Lee, Guy Dumas, Peter Oshkai

Bibliographic record

VenuePhysics of Fluids · 2024
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsUniversité LavalUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsVortexMechanicsDynamics (music)Computational fluid dynamicsTurbineClassical mechanicsAerospace engineeringAcoustics

Abstract

fetched live from OpenAlex

The present work assesses the use of spanwise flow in enhancing the performance of the fully passive oscillating-plate hydrokinetic turbine prototype by relating the dynamics of the leading edge vortex (LEV) to the power extraction performance. Two-dimensional (2D) planar and three-dimensional (3D) tomographic particle image velocimetry were employed to obtain quantitative flow structure of oscillating-plates undergoing heave and pitch motion in uniform inflow at Reynolds number of 21 000. A plate with a 6° sweep angle and an unswept plate (control case) were considered in the present study. Dynamics of the LEV were investigated using the patterns of the phase-averaged vorticity during the oscillation cycle. The 3D vector fields provided insights into the spanwise variation of the vortical structure and the rate of deformation of the vortex, which was determined by calculating the deformation terms in the vorticity transport equations which are related to the stability of the vortex. The results show evidence of a delay in the shedding of the LEV and an increase in its stability in the case of the swept plate, compared to the control case, which in turn benefit the power extraction performance at high inflow velocities.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.668

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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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 designBench or experimental
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

Citations1
Published2024
Admission routes2
Has abstractyes

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