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Record W4378965594 · doi:10.18280/jesa.560208

Performance of Axial Generator for a Small Vertical Axis Wind Turbine

2023· article· fr· W4378965594 on OpenAlexvenueno aff
Toto Rusianto, Saiful Huda, Sudarsono Sudarsono, Muhammad Suyanto

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2023
Typearticle
Languagefr
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsnot available
FundersDirektorat Jenderal Pendidikan TinggiKementerian Pendidikan, Kebudayaan, Riset, dan Teknologi
KeywordsVertical axis wind turbineVertical axisHorizontal axisGenerator (circuit theory)TurbineWind powerMarine engineeringWind generatorGeologyPhysicsElectrical engineeringAerospace engineeringEngineeringStructural engineeringPower (physics)Engineering drawing

Abstract

fetched live from OpenAlex

This paper presents an investigation of an axial generator for a small vertical-axis wind turbine.The performance of the axial generator design is tested by knowing the output voltage produced by varying the rotation.The generator is designed to generate three phases of electric power.And then through the wind turbine controller, three phases of alternating current are converted into direct current/DC.The Axial generator uses neodymium permanent magnets with many winding poles of 12 pieces.The coil uses 0.5 mm diameter copper enamel wire with a total of 400 turns each.A voltage of 30 Volt DC is obtained for the rotation of the axial generator at 300 rpm.For application, the generator can be used for a small vertical-axis wind turbine for stand-alone street lighting, which needs only 12 Volt of DC.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0040.001

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 head0.028
GPT teacher head0.251
Teacher spread0.222 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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