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Numerical and Experimental Test on an Innovative Device Based on Multiple Rotors in Line to Tap Clean Energy from Tidal and River Current

2016· article· en· W2547824681 on OpenAlexvenueno aff
Domenico Coiro, Fabio Scherillo, G. Troise, Nadia Bizzarrini, Giuseppe Calise

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2016
Typearticle
Languageen
FieldComputer Science
TopicEnvironmental Engineering and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarine engineeringTowingEngineeringCurrent (fluid)SubmarineTidal powerTurbineScale modelTest (biology)Mechanical engineeringAerospace engineeringElectrical engineeringGeology

Abstract

fetched live from OpenAlex

The main object of this paper is to present the design and the results of an experimental test campaign on an innovative device for the exploitation of marine and river currents. The basic idea is to lay together one or more series of horizontal axis turbines in rows, each one connected to a generator placed on board a ship or a float. The whole system is sustained by a series of buoys, in this way is possible to avoid expensive submarine installations. All the work has been carried out at the Department of Industrial Engineering of the University of Naples "Federico II" and the test campaign has been first performed in the naval towing tank belonging to the same Department and then in real conditions in Messina Strait between Sicily island and mainland. This location is the only one in Italy suitable as test site thanks to a highly regular tidal current reaching a maximum speed of 3 m/s. The turbine's blade was first carefully designed with particular care for the cavitation problems. Two different series of experimental tests on a reduced scale model in the naval tank aimed to optimize the general layout of the device and the tests performed in Messina Strait mainly aimed to confirm the feasibility of the system and to evaluate its response in real operating conditions. The tests have confirmed the good dynamic behavior of the whole system and its feasibility to be scaled up to real scale.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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 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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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