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Record W2558036773 · doi:10.4043/27355-ms

Investigation and 3D Discrete Element Modeling of Fracture of Sea Ice Beams

2016· article· en· W2558036773 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueArctic Technology Conference · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsMemorial University of Newfoundland
FundersHibernia Management and Development CompanyResearch and Development Corporation of Newfoundland and Labrador
KeywordsFlexural strengthRubbleSea iceDiscrete element methodGeologyStructural engineeringShear (geology)Beam (structure)BendingGeotechnical engineeringMaterials scienceEngineeringMechanics

Abstract

fetched live from OpenAlex

Abstract Flexural failure of sea ice is of interest in many different applications, ranging from understanding rubble formation processes to modeling bending failure of ice sheets against sloped structures and ship hulls. In this paper we present a brief summary of recent in-situ experiments carried out on side-loaded sea ice beam specimens on the ice fields near Storfjorden, Svalbard. Results from these tests have been used to parameterize a discrete element model of ice fracture under flexural loading. Simulations of these experiments in 3D have been carried out using a new material model within the open-source Discrete Element Method (DEM) code WooDEM which features cohesive bonds in tension, shear, flexure and torsion based on a contact model with normal, shear, torsional and flexural springs. A comparison of simulated and field test results, along with recommendations for future work is 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.279

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 head0.014
GPT teacher head0.206
Teacher spread0.192 · 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