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Record W2326116016 · doi:10.1115/fedsm-icnmm2010-30148

Effect of Chordwise Flexibility and Depth of Submergence on an Oscillating Plate Underwater Propulsion System

2010· article· en· W2326116016 on OpenAlexaff
Oleksandr Barannyk, Bradley J. Buckham, Peter Oshkai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsStrouhal numberThrustPropulsorPropulsive efficiencyPropulsionKinematicsReynolds numberOscillation (cell signaling)MechanicsUnderwaterAcousticsPhysicsMarine engineeringAerospace engineeringEngineeringGeologyClassical mechanicsTurbulence

Abstract

fetched live from OpenAlex

This work was dedicated to the experimental study of oscillating plate propulsors undergoing a combination of heave translation and pitch rotation. The oscillation kinematics are inspired by swimming mechanisms employed by fish and other marine animals. The primary focus was on the propulsive characteristics of such oscillating plates, which were studied by means of direct force measurements in the thrust-producing regime. Experiments were performed at constant Reynolds number and constant heave amplitude. By varying the Strouhal number, the depth of submergence and the chordwise flexibility of the plate, it was possible to investigate corresponding changes in the generated thrust and the hydromechanical efficiency. It was possible to establish a set of parameters, including the driving frequency of the system, the ratio of rigid to flexible segment length of the plate, and the range of Strouhal numbers that led to a peak efficiency of approximately 80%. The experiments involving plates with various ratios of rigid to flexible segment lengths showed that greater flexibility increased the propulsive efficiency and thrust compared to an identical motion of the purely rigid plate. By submerging the plate at different depths, it was observed that the proximity of the propulsor to the bottom of the channel led to overall increase in the thrust coefficient.

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)0.001
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 score0.070
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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