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Record W6999936925

2-Dimensional edge crushing tests on thick sections of ice confined at the section faces

2008· article· en· W6999936925 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2008
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsBritish Columbia Institute of TechnologyNational Research Council CanadaCommunity Sector Council Newfoundland and Labrador
Fundersnot available
KeywordsBorosilicate glassEnhanced Data Rates for GSM EvolutionPressure measurementCross section (physics)Pressure vesselScale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

A crushing apparatus incorporating the novel characteristics of the apparatus used by Gagnon and Bugden (2007), and fabricated at 3 times the scale, has been used to conduct crushing experiments on polycrystalline ice, large single crystals of ice and iceberg ice at -10°C. The results confirmed that the behaviours of the different ice types were essentially invariant for the change of scale and that the apparatus functioned as intended at the larger scale, that is, it provided visual data of a 2-D slice of ice during crushing as though it was part of a larger piece of ice. Rectangular thick sections (3 cm thickness) of ice were confined between two thick borosilicate glass plates and crushed from one edge face at a rate in the range 1.5 - 2.5 cm/s using a transparent acrylic platen (3 cm thickness) inserted between the plates. Three identical pressure sensors, of the same type used before, were placed side-by-side to measure pressure across the full breadth of the platen/ice contact area between the glass plates as the samples were being crushed. The pressure data corroborated with the smaller-scale pressure data from the earlier tests and the apparatus served as a test bed to demonstrate that the pressure-sensing technology could function effectively in the side-by-side configuration. This technology will be used to obtain high spatial resolution pressure data during an upcoming full-scale study of ship / bergy bit impacts within the next few years.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.262

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 head0.022
GPT teacher head0.223
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2008
Admission routes2
Has abstractyes

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