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Record W2152678794 · doi:10.1109/cjece.2006.259175

Potential and electric-field distributions around an ice-covered post-type insulator

2006· article· en· W2152678794 on OpenAlexaffvenue
C. Volat, M. Farzaneh

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsInsulator (electricity)Electric fieldArc flashMaterials scienceMechanicsGeologyComposite materialPhysics

Abstract

fetched live from OpenAlex

To facilitate the study of phenomena preceding the flashover of an ice-covered station post insulator during a melting period, the potential and electric-field distributions along the insulator have been numerically calculated. Commercial software based on the boundary element method was used for this purpose, and a simplified three-dimensional model of the ice-covered insulator was developed and validated experimentally. Then, a station post insulator covered with wet-grown ice under a melting regime was numerically simulated on the basis of experimental results. The presence of a conducting water film at the ice surface, the shedding of ice deposits, and the presence of a partial electric arc along an air gap were taken into account in the simulations. The results obtained have made it possible to show that the water film, the number of intervals of air, and the presence of partial arcs have a considerable effect on the distribution of the potential and the electric field along the insulator. In the same way, the appearance of a partial arc as well as the occurrence of ice shedding lead to a redistribution of the potential along the ice deposit, either supporting or inhibiting the flashover process. The results obtained will help to improve insulator geometry for cold climate regions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.534

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 head0.003
GPT teacher head0.156
Teacher spread0.153 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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