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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 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 categoriesInsufficient payload (model declined to judge)
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 score0.017
Threshold uncertainty score1.000

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)0.0010.000

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 head0.016
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 teacher head, not a consensus.

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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