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Record W3158092848 · doi:10.1049/rpg2.12192

Rotors for wave energy conversion—Practice and possibilities

2021· article· en· W3158092848 on OpenAlexfundno aff
Andrei Ermakov, John V. Ringwood

Bibliographic record

VenueIET Renewable Power Generation · 2021
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsnot available
FundersQueen's UniversityQueen's University BelfastEuropean Commission
KeywordsEnergy transformationEnergy (signal processing)Computer scienceNuclear engineeringEnvironmental sciencePhysicsEngineeringThermodynamics

Abstract

fetched live from OpenAlex

Abstract This review studies some of the existing ideas which create a fundamentally new direction for wave energy converter (WEC) development, obtaining energy from the elliptical motion of particles in water waves using a rotor. The review focuses on three main aspects of rotor‐based WECs: experimental study of the developed prototypes, derivation and development of the mathematical models, and control effectors and philosophies for the proposed devices. The range of developed small scale prototypes and their experimental studies are presented. The shortcomings of the current mathematical and hydrodynamic models are identified, while an overview of the proposed and new possible control effectors and strategies is conducted. This allows us to see the state of the development of the different concepts and problems to be solved in bringing wave energy rotors to operational reality.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.210
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations25
Published2021
Admission routes1
Has abstractyes

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