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Experimental investigation on the tensile strength of freshwater freeze-bonds

2023· article· en· W4323978386 on OpenAlexafffund
Soroosh Afzali, Rocky Taylor, Robert Sarracino

Bibliographic record

VenueCold Regions Science and Technology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCentre For Cold Ocean Resources EngineeringMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUltimate tensile strengthBond strengthMaterials scienceRubbleComposite materialSubmersion (mathematics)Compressive strengthGeotechnical engineeringGeologyLayer (electronics)

Abstract

fetched live from OpenAlex

The strength of the freeze-bonds between ice blocks has been found to significantly affect the strength and failure mechanism of ice rubble and ice ridges. Limited information on the tensile strength of freeze-bonds is presently available. A new testing apparatus and method has been developed to study the tensile strength of freeze-bonds under submerged, confined conditions as expected in natural ice ridges and rubble. A total of 30 experiments have been carried out to study the effect of normal confinement pressure and submersion time on the tensile strength of freshwater freeze-bonds. The confinement pressures ranged from 25 kPa to 100 kPa and freeze-bonds formed in 5 min to 3 h of submersion. The strength of freeze-bonds has been found to increase with the increase of the confinement pressure. The development of the tensile strength of freeze-bonds by submersion time was found to be similar to the development of the freeze-bond shear strength. Empirical equations for estimation of the freeze-bond strength as a function of confinement pressure is presented.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
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 head0.023
GPT teacher head0.220
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 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
Published2023
Admission routes2
Has abstractyes

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