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Record W6947754635 · doi:10.4224/8895076

Preliminary modelling of ship manoeuvring in ice using a PMM

2006· report· en· W6947754635 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2006
Typereport
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsMathematical modelMoment (physics)Numerical modelingSeries (stratigraphy)Numerical models

Abstract

fetched live from OpenAlex

The Institute for Ocean Technology (IOT) of the National Research Council of Canada (http://www.iot-ito.nrc-cnrc.gc.ca/) has conducted physical, numerical and mathematical modeling of ship manoeuvring characteristics in ice, as part of a larger effort to develop reliable modeling techniques to assist in the design of new ice-worthy vessels and in the simulation of their navigating characteristics. This report presents results from a preliminary series of physical and mathematical modeling of the problem. The report focuses on the interaction processes and the influence of ship motions on the yaw moment exerted on the ship hull. The dominant ice-ship interaction processes are identified. The results show a large influence of ship motions and interaction geometry on the measured yaw moments. The geometrical aspect of the interaction processes is described and its influences on ice loads are discussed. Conclusions are made and recommendations for future works are provided.

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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.053
GPT teacher head0.255
Teacher spread0.202 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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