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Record W1591353763

Best practice guidelines for tank testing of wave energy converters

2009· article· en· W1591353763 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStrathprints: The University of Strathclyde institutional repository (University of Strathclyde) · 2009
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilQueen's University BelfastQueen's UniversityScottish Funding Council
KeywordsWave energy converterMarine engineeringEnergy (signal processing)Energy transformationEngineeringSubmarine pipelineCurrent (fluid)ConvertersWave tankMechanical engineeringReliability engineeringElectrical engineeringPhysicsMechanicsGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Experimental tank testing is a key aspect of wave energy conversion research. The performance of designs can be assessed in an accessible and controlled environment and at a fraction of the cost of sea trials. Wave energy converter (WEC) tank testing is complex and has its own specificities compared with model testing of ships and offshore structures. This largely reflects the fact that the main quantity of interest is wave energy: how much is available and how much is harvested by the model. This paper provides an extensive overview of the various aspects of WEC tank testing. These are divided into three categories: physical model, measurements, and wave generation. For each of them, current best practice guidelines are given.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.043
GPT teacher head0.221
Teacher spread0.178 · 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