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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 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.460
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.067
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