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Record W2010142836 · doi:10.1080/14786451.2014.932282

A cascade model of blade element interaction for wind turbines with unequal blades

2014· article· en· W2010142836 on OpenAlexafffund
David Wood

Bibliographic record

VenueInternational Journal of Sustainable Energy · 2014
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCascadeBlade (archaeology)Wind powerTurbine bladeEngineeringStructural engineeringAerospace engineeringMarine engineeringPhysicsTurbineElectrical engineering

Abstract

fetched live from OpenAlex

Horizontal-axis wind turbines often operate with unequally performing blades. A simple extension of blade element analysis for unequal blades is developed using the two-dimensional cascade analogue of wind turbines. The vortex strengths of the blade elements can vary with blade number. For three-bladed rotors, the unequal strengths induce an extra velocity at each blade, but for two blades there is no additional velocity. For both blade numbers, there is a modification to the rotational inflow factor. To determine the significance of blade differences, test calculations are presented for two- and three-bladed turbines with different blade pitch angles. The modifications proposed here do not substantially alter the calculations of turbine power and thrust near the point of maximum performance. However, some substantial differences were found at higher thrust. Furthermore, the new method predicts much larger variations in the blade element torque between the blades in the hub region for most operating conditions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.513
Threshold uncertainty score0.377

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)0.0000.000

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 head0.009
GPT teacher head0.238
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2014
Admission routes2
Has abstractyes

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