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Record W2012685088 · doi:10.1115/omae2004-51267

Evaluation of Mechanisms of Ice Adhesion on Power Network Equipment

2004· article· en· W2012685088 on OpenAlexafffund
Mohammad Reza Kasaai, M. Farzaneh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversité du Québec à Chicoutimi
KeywordsMaterials scienceAdhesionCeramicPenetration (warfare)van der Waals forceComposite materialBond strengthChemical physicsAdhesiveMoleculeChemistry

Abstract

fetched live from OpenAlex

The objective of this study is to review the mechanisms of ice adhesion to cables and insulators, with a special emphasis on aluminum and ceramic materials, as these devices are made from these materials. This review shows that the physico-chemical interactions and mechanical interlock contribute to the mechanisms of ice adhesion to surfaces. The physico-chemical mechanisms of ice adhesion to surfaces are classified into three main categories: dipole-dipole or ion-dipole interactions; hydrogen bond; and van der Waals interactions. The interfacial adhesion strength of ice/metals or ice/ceramic insulators is greater than the strength of ice. This indicates that the strength between ice and the material surfaces is greater than hydrogen bonds of ice itself. The mechanical mechanism involves the penetration of liquid water into cavities and pores on the surface of the substrate and expansion of ice during solidification, resulting in an anchor effect and the establishment of a strong bond between ice and surface.

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)0.001
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 score0.919
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.253
Teacher spread0.227 · 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

Citations6
Published2004
Admission routes2
Has abstractyes

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