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Record W3212841372 · doi:10.1063/5.0102388

A survey of two analytical wake models for crosswind kite power systems

2022· article· en· W3212841372 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysics of Fluids · 2022
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsConcordia UniversityQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCrosswindWakeKiteAerodynamicsComputational fluid dynamicsPhysicsAerospace engineeringFlow (mathematics)Wind powerMechanicsMarine engineeringMeteorologyApplied mathematicsClassical mechanicsMathematicsEngineeringGeometry

Abstract

fetched live from OpenAlex

This paper presents two novel analytical wake models for crosswind kite power systems. One is developed based on the continuity equation, and the other is based on both the continuity and momentum equations. For each model, equations for the wake flow speed and the wake shape are obtained through a rigorous theoretical approach. Wake models for crosswind kites provide a first step in the understanding of the effects of kite-to-kite aerodynamic interactions on prospective wind energy kite farms. Despite a fair number of computational studies on these wakes, few studies have attempted to provide a concrete analytical solution. The primary motivation of this study comes from the fact that analytical models are simple in form and require very little computational power when being solved. The results from the two analytical models are compared with each other and are verified against computational results. Bearing several assumptions, these models are meant to simply offer a preliminary insight that will hopefully see many improvements with added complexity in the near future.

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.

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 score0.506
Threshold uncertainty score0.638

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 head0.029
GPT teacher head0.248
Teacher spread0.219 · 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