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Control of propeller cavitation in operational conditions

2010· article· en· W1578548769 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

VenueJournal of Marine Engineering & Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsnot available
FundersDefence Research and Development Canada
KeywordsPropulsionPropellerMarine engineeringCavitationNavyMarine propulsionSea trialEngineeringAeronauticsFull scaleAutomotive engineeringEngine roomAerospace engineeringMechanical engineeringStructural engineeringAcoustics

Abstract

fetched live from OpenAlex

Off-design conditions can have a severe impact on ship propulsion system behaviour. Resistance increase, for instance, leads to higher engine loading, and can also easily lead to a decrease of cavitation inception speed with respect to calm water conditions. Wakefield variations due to ship motions, waves and manoeuvres also have an effect on engine loading and on propeller cavitation. This paper discusses the model-based development of a propulsion control system aiming at increased cavitation free time in operational conditions, while preventing engine overloading and keeping manoeuvring characteristics acceptable. The developed propulsion control system was tested extensively in a simulation environment before full-scale trials took place in February 2008, onboard a Royal Netherlands Navy frigate. Results in terms of full-scale propulsion system behaviour are presented, including photos showing the propeller cavitation behaviour in operational conditions.

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: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.003
GPT teacher head0.191
Teacher spread0.189 · 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