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Record W1963861588 · doi:10.1115/fedsm2012-72089

3D Unsteady Simulation of a Planing Hull Propelled by a Waterjet Pump System

2012· article· en· W1963861588 on OpenAlexafffund
Simon Forest, Stéphane Moreau, Alain Desrochers

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicShip Hydrodynamics and Maneuverability
Canadian institutionsUniversité de Sherbrooke
FundersCompute CanadaUniversité de Sherbrooke
KeywordsHullPropulsionMarine engineeringDuct (anatomy)Computational fluid dynamicsRobustness (evolution)MechanicsInletEngineeringSimulationMechanical engineeringAerospace engineeringControl theory (sociology)Computer sciencePhysicsControl (management)

Abstract

fetched live from OpenAlex

A comprehensive modeling of the physics and dynamics of a realistic planing boat has been simulated. This study considers a two degree-of-freedom (DOF) unsteady model to investigate the equilibrium of the boat at steady speed and mimic the system dynamics properly. The numerical model consists of a planing hull with a waterjet pump inlet duct and a mathematical representation of the main forces and mass flow to model the pump. Indeed, it includes the interaction of the hull and the waterjet propulsion system, which has never been done before. The mathematical model of the pump is based on a full 3D unsteady simulation of a reduced control volume of the propulsion system. The numerical robustness and accuracy have been confirmed after being compared to other studies and to a prototype boat. Finally, the results provide a novel 3D unsteady numerical model of the equilibrium of a planing hull at a steady speed, including the effect of the waterjet pump.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.202
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 designSimulation or modeling
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".

Quick stats

Citations1
Published2012
Admission routes2
Has abstractyes

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