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Record W2020778551 · doi:10.1260/030952407781998800

Desirable Airfoil Features for Smaller-Capacity Straight-Bladed VAWT

2007· article· en· W2020778551 on OpenAlexaff
Mazharul Islam, David S.‐K. Ting, Amir Fartaj

Bibliographic record

VenueWind Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAirfoilVertical axis wind turbineAerodynamicsTurbineLift (data mining)Aerospace engineeringMarine engineeringEngineeringStructural engineeringMechanical engineeringComputer science

Abstract

fetched live from OpenAlex

In the small scale wind turbine market, the simple straight-bladed Darrieus type vertical axis wind turbine (SB-VAWT) is very attractive for its simple blade design. A detailed aerodynamic performance analysis was conducted on a smaller capacity fixed-pitch SB-VAWT. Brief analyses of the main aerodynamic challenges of this type of wind turbine were first discussed and subsequently the authors conducted further literature survey and computational analysis to shortlist aerodynamic characteristics of a desirable airfoil for a self-starting and better performing SB-VAWT. The required geometric features of the desirable airfoil to achieve the short listed characteristics were also discussed. It has been found out that conventionally used NACA symmetric airfoils are not suitable for smaller capacity SB-VAWT. Rather, it is advantageous to utilize a high-lift and low-drag asymmetric thick airfoil suitable for low speed operation typically encountered by SB-VAWT.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.205
Teacher spread0.187 · 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

Citations90
Published2007
Admission routes1
Has abstractyes

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