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Record W4324373432 · doi:10.1177/00375497221151188

Discrete event simulation of vessel stationkeeping operations in ice-rich waters

2023· article· en· W4324373432 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.

Bibliographic record

VenueSIMULATION · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCommunity Sector Council Newfoundland and Labrador
Fundersnot available
KeywordsPropellerSea iceRange (aeronautics)FidelityComputer scienceSimulationEvent (particle physics)Marine engineeringGeologyAerospace engineeringEngineeringPhysicsOceanography

Abstract

fetched live from OpenAlex

This paper describes a high-fidelity numerical model that simulates vessel stationkeeping operations in ice-rich waters. The discrete event simulation engine incorporates several novel features, including new ice floe failure models for bow and midships locations; an ice floe creation strategy that facilitates rafting of ice floes; and a vessel thruster model that takes into account physical limitations such as thruster angle slew rates and propeller ramp rates. It accommodates a wide range of ice field specifications and runs in real-time on a standard desktop personal computer (Intel ® Core™ i7 Processor or equivalent). The model has been validated using physical measurements of a generic drillship model in several broken ice conditions; it predicted thruster forces and motions that were comparable to those observed during dynamic positioning operations.

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 score0.191
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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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