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Record W2048749464 · doi:10.1115/imece2013-63367

Design Criteria on Sizing and Material Selection of SB-VAWTS

2013· article· en· W2048749464 on OpenAlexafffund
Mojtaba Ahmadi-Baloutaki, Rupp Carriveau, David S.‐K. Ting

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolidityRotor (electric)Moment of inertiaSizingTurbineBlade (archaeology)Rotational speedTurbine bladeWind powerStructural engineeringBending momentAspect ratio (aeronautics)Material selectionMaterials scienceMoment (physics)Tip-speed ratioInertiaMechanical engineeringEngineeringComputer sciencePhysicsComposite materialChemistryElectrical engineering

Abstract

fetched live from OpenAlex

A design methodology has been presented on the sizing and material selection of straight-bladed vertical axis wind turbines. Several design parameters such as turbine power coefficient, blade tip speed ratio, rotor solidity factor, blade aspect ratio and rotor moment of inertia have been analyzed. Material selection and its relevant design criteria have also been discussed for different parts of a straight-bladed vertical axis wind turbines with three blades and two supporting arms per blade. The number of the supporting arms and their optimum locations have been determined via minimizing the bending moments on the blade. A comparative study has also been performed to examine the effect of blade density and turbine H/D ratio on the rotor moment of inertia. It was found that the turbine rotational speed increases as blade density decreases and this increase is larger at higher turbine H/D ratio.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.016
GPT teacher head0.221
Teacher spread0.204 · 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

Citations1
Published2013
Admission routes2
Has abstractyes

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