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Record W4392170648 · doi:10.1063/5.0183523

Propeller–hull interaction simulation for self-propulsion with sinkage and trim

2024· article· en· W4392170648 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 · 2024
Typearticle
Languageen
FieldEngineering
TopicShip Hydrodynamics and Maneuverability
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHullPropellerTrimPropulsionPropulsorMarine engineeringPhysicsMarine propulsionRigid bodyComputational fluid dynamicsTransverse planeAerospace engineeringMechanicsAdvance ratioEngineeringStructural engineeringBlade pitchClassical mechanics

Abstract

fetched live from OpenAlex

This paper presents numerical simulations of propeller–hull interaction of a ship model for the dynamic condition, demonstrating the ability of the developed self-propulsion module in OpenFOAM. A dynamic motion class has been developed based on the sliding mesh method to simulate a rotating propeller with ship motions. A body-force method is also implemented to simulate propeller–hull interaction to reduce the computational cost of propeller modeling. Validation studies were carried out for the Japan Bulk Carrier (JBC) ship model. The bare-hull resistance, sinkage, and trim are verified against the experimental data. The propeller open-water hydrodynamic characteristics are then computed and validated using sliding mesh and body-force methods. Finally, the self-propulsion simulations are carried out for the JBC model in calm water with sinkage and trim at the design speed. Numerical predictions of the self-propulsion parameters and axial flow velocity distributions at different transverse locations are presented.

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 score0.337
Threshold uncertainty score0.268

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 head0.012
GPT teacher head0.250
Teacher spread0.238 · 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