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Record W2523015208

Friction of Sea Ice On Steel For Condition of Varying Speeds

2002· article· en· W2523015208 on OpenAlexaff
R. Frederking, Anne Barker

Bibliographic record

VenueThe Twelfth International Offshore and Polar Engineering Conference · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCanadian Cardiovascular Society
Fundersnot available
KeywordsSea iceStatic frictionKinetic energyGeologyFriction coefficientMechanicsCoefficient of frictionMaterials scienceGeotechnical engineeringComposite materialPhysicsClimatologyClassical mechanics
DOInot available

Abstract

fetched live from OpenAlex

A testing system has been devised to simulate the frictional behaviour between ice and a structure as the ice slows down and stops, and subsequently increases in speed again. This simulates the interaction behaviour often observed in nature between ice floes and a sloping structure. A test series was carried out to measure friction between sea ice and smooth painted steel and heavily corroded steel under the condition of continuously varying velocities ranging from 0 to 0.3 m/s. The results of the tests on smooth painted steel showed that the kinetic coefficient of friction increased progressively from 0.04 at 0.1 m/s to 0.08 when the ice stopped. The static friction to start moving the ice again was about 0.25. For corroded steel the kinetic coefficient of friction increased progressively from 0.14 at 0.1 m/s to 0.20 when the ice stopped. The static friction to start moving the ice again was about 0.45. These values of friction coefficient can be used in simple ice load calculation algorithms or more complex numerical simulations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.364

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 head0.020
GPT teacher head0.216
Teacher spread0.196 · 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.

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

Citations17
Published2002
Admission routes1
Has abstractyes

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