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Record W2627068195

Forces On Ships Transiting Pressured Ice Covers

2011· article· en· W2627068195 on OpenAlexaffvenueabout
Mohamed Sayed, Ivana Kubat

Bibliographic record

VenueNPARC · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCanadian Cardiovascular Society
Fundersnot available
KeywordsEnvironmental scienceGeologyMeteorologyAeronauticsEngineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

The paper describes numerical simulations of ship transit through pressured ice conditions. The numerical model solves the equations of the conservation of mass and linear momentum together with constitutive equations representing plastic yield. That yield envelope is based on a cohesive Mohr-Coulomb criterion with a tension cut-off. The numerical solution employs a hybrid Lagrangian-Eulerian formulation. Pressured ice conditions are constructed by allowing a shear stress (e.g. representing wind drag) to compress an ice cover of initial uniform thickness against a straight land boundary. A ship is then introduced and moves parallel to the land boundary at constant velocity. The geometry of the Canadian Coast Guard vessel, CCGS Louis S. St- Laurent, is used in the tests. The results give the total force on the ship under a range of confining ice pressures. The distributions of ice concentration, thickness and pressures are also obtained. The simulation results show that both the velocity of the ship, and magnitude of confining pressure have significant effects on ice force. The results also examine the dependence of ice forces on ship velocity and ice thickness. Copyright © 2011 by the International Society of Offshore and Polar Engineers (ISOPE).

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.995

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)0.0060.000

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 head0.025
GPT teacher head0.196
Teacher spread0.171 · 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 teacher head, not a consensus.

Study designObservational
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

Citations10
Published2011
Admission routes3
Has abstractyes

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