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Record W4200247249 · doi:10.5750/ijme.v161ia1.1080

INTERNATIONAL DEVELOPMENT AND VALIDATION OF A DISTRIBUTED SIMULATION FOR NAVAL SHIP REPLENISHMENT AT SEA

2021· article· en· W4200247249 on OpenAlexaffabout
Kevin McTaggart, D Tozzi, Gilles Henry, Federicia Valdenazzi, Norbert Stuntz

Bibliographic record

VenueThe International Journal of Maritime Engineering · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsPayload (computing)Marine engineeringDistributed Interactive SimulationSoftwareHigh-level architectureSea trialComputer scienceSimulation softwareModeling and simulationSynchronization (alternating current)Systems engineeringSimulationEngineeringInteroperabilityTelecommunications

Abstract

fetched live from OpenAlex

Navies from Canada, France, Germany, Italy, and the United Kingdom collaborated to develop and validate a distributed simulation of ship replenishment at sea. The simulation models the seaway, ship motions including hydrodynamic interaction effects between ships, and the transfer of a solid payload between ships using replenishment gear. The simulation was developed using the High Level Architecture (HLA), which facilitates sharing of data and synchronization of simulation time among software components on networked computers. Simulation results were validated using experimental data. The project demonstrated successful application of distributed simulation to complex naval platform systems. Lessons learned are shared for several areas, including seaway modelling, ship hydrodynamic interaction, and planning of model tests and sea trials for simulation validation.

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)0.004
metaresearch head score (Gemma)0.004
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: Methods · Consensus signal: Methods
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.067
GPT teacher head0.365
Teacher spread0.298 · 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
GenreMethods

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

Citations0
Published2021
Admission routes2
Has abstractyes

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