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Record W7038324414

Ice crushing and cyclic loading in compression

2008· article· en· W7038324414 on OpenAlexfundvenueno aff

Bibliographic record

VenueNPARC · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSofteningRecrystallization (geology)Hardening (computing)CreepCompression (physics)Dynamic recrystallization
DOInot available

Abstract

fetched live from OpenAlex

At very slow loading rates, ice will creep; as the rate is increased, microstructural changes occur and the rate of creep is enhanced as a result. These microstructural changes are referred to as 'damage'. As the rate of loading is increased further, the damage becomes localized into a layer adjacent to the indentor. This layer is associated with 'high-pressure zones' (hpz's). A bulb of pressure develops over these zones with values up to 100 MPa at the centre. Processes within the layer vary with distance from the centre; microfracturing and recrystallization occur near the outside with recrystallization and pressure melting (it is supposed) along grain boundaries in the central part. Cyclic loading can result since the cycle of pressure softening and subsequent hardening upon release of the pressure results in a repetitive cycle. An analysis has been performed using the ABAQUS computer program that encapsulates the principal features of the process. Some results of this analysis are given. It is also shown that the mechanics can be scaled geometrically without any basic change. This explains why the hpz's are found over widely differing scales. Laboratory and field data involving cyclic loading, including Molikpaq and medium scale data, are reviewed and discussed in the context of feedback mechanisms and ice-induced vibration. Finally, data and results from impact tests on other materials, as well as dynamic recrystallization at high speeds are reviewed and discussed in the context of ice compressive failure.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.653

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)0.0010.000

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 head0.017
GPT teacher head0.210
Teacher spread0.193 · 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 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

Citations9
Published2008
Admission routes2
Has abstractyes

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