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Record W3194045536 · doi:10.11159/htff21.136

A Re-examination of Power Coefficient as a Measure of Performance for Horizontal Axis Wind Turbines

2021· article· en· W3194045536 on OpenAlexvenueno aff
Thomas M. Adams, Benjamin Mertz

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsnot available
Fundersnot available
KeywordsHorizontal axisWind powerMeasure (data warehouse)Horizontal and verticalPower (physics)Vertical axisMarine engineeringEnvironmental scienceAcousticsGeologyGeodesyComputer scienceEngineeringElectrical engineeringPhysicsEngineering drawingStructural engineering

Abstract

fetched live from OpenAlex

Linear momentum theory as applied to horizontal axis wind turbines (HAWTs) provides perhaps the most useful basis for understanding their operation. In particular, the theoretically derived expression for power coefficient represents a convenient measure of performance, as well as provides insight into optimal operating conditions. The typical interpretation of power factor as an energy conversion efficiency, however, especially in the context of converting the "power in the wind" to a power output, has several conceptual difficulties. In this paper it is argued that the energy efficiency interpretation of power coefficient can be misleading, potentially leading to misinterpretation of performance of different wind turbine designs. Instead, an interpretation of power coefficient as the "relative capture area" of a wind turbine is suggested, analogous to the relative capture width parameter for ocean wave energy conversion devices. Such an interpretation gives a more physically coherent picture of wind turbine performance and provides a more pragmatic measure of performance, one that can also be applied to other wind machine designs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.529

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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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 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
Published2021
Admission routes1
Has abstractyes

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