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Record W2120581411 · doi:10.1109/ccece.2006.277821

A Technology Review and Simulation Based Performance Analysis of River Current Turbine Systems

2006· review· en· W2120581411 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of NewfoundlandAtlantic Canada Opportunities Agency
KeywordsComputer scienceMATLABTurbineCurrent (fluid)Rotor (electric)ElectricityConvertersDomain (mathematical analysis)Industrial engineeringHydraulic turbinesSystems engineeringControl engineeringMarine engineeringMechanical engineeringEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

River current turbines are electromechanical energy converters that harness kinetic energy of a stream of flowing river water to generate electricity. Research in this domain is limited and various concepts are emerging only recently. In this paper, an extensive technology survey and comparison of various system options are discussed in order to formulate a basis for further analysis. Simplified mathematical modeling of an augmentation device and Darrieus type rotor has been carried out. Simulations are done in Matlab and results are given with graphical interpretations. In conclusion, directions for further investigation are given and the potential of this technology is re-stressed

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.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.677
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
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 head0.025
GPT teacher head0.279
Teacher spread0.253 · 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

Quick stats

Citations53
Published2006
Admission routes2
Has abstractyes

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