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Record W2155955797 · doi:10.1109/naps.2008.5307306

Tow tank testing and performance evaluation of a permanent magnet generator based small vertical axis hydrokinetic turbine

2008· article· en· W2155955797 on OpenAlexaff
M.J. Khan, M. Tariq Iqbal, John E. Quaicoe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsMemorial University of NewfoundlandPowertech Labs (Canada)
FundersRiphah International University
KeywordsVertical axisPermanent magnet synchronous generatorMagnetRotor (electric)TurbineMarine engineeringGenerator (circuit theory)RippleElectricity generationMechanical engineeringAutomotive engineeringEnvironmental scienceEngineeringPower (physics)Electrical engineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

Vertical axis turbines using permanent magnet generators are being considered as options for use in hydrokinetic energy conversion. As a precursor to development of full-scale systems, scale-model turbines need to be tested in controlled environment. In this article, the results of tow tank testing of a small vertical axis turbine employing a permanent magnet generator are presented. Effects of rotor submersion, ripple propagation, and start-up behavior are presented along with relevant qualitative discussions. Results indicate an overall peak conversion efficiency of 22%. The critical limitations of these tests and general observations are also summarized at the end of this paper.

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 score0.246
Threshold uncertainty score0.343

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 head0.044
GPT teacher head0.224
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 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

Citations10
Published2008
Admission routes1
Has abstractyes

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