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Record W2138040282 · doi:10.1002/hyp.5807

Experimental study and mathematical modelling of flashover on extra‐high voltage insulators covered with ice

2004· article· en· W2138040282 on OpenAlexafffundabout
J. Farzaneh‐Dehkordi, J. Zhang, M. Farzaneh

Bibliographic record

VenueHydrological Processes · 2004
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaHydro-QuébecUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsArc flashIcingInsulator (electricity)VoltageElectric arcEnvironmental scienceHigh voltageElectric power transmissionElectrical engineeringMeteorologyMaterials scienceAtmospheric sciencesEngineeringGeologyPhysicsElectrode

Abstract

fetched live from OpenAlex

Abstract Using a test method developed at the high‐voltage laboratory of the NSERC/Hydro‐Quebec/UQAC Industrial Chair on Atmospheric Icing of Power Network Equipment (CIGELE), the relation between the minimum flashover voltage V MF and the insulator dry arcing distance for standard porcelain station post insulators, as typically used in Hydro‐Quebec substations, was investigated under icing conditions. The experimental results show that, under wet‐grown ice, known as the most dangerous type of ice for power transmission systems, the V MF increases nonlinearly with an increase in insulator length. Based on these results, an improved mathematical model for predicting the critical flashover voltage versus length of ice‐covered insulators is presented. This model is helpful for understanding the flashover phenomenon on ice‐covered insulators and presents a powerful tool for choosing the proper length of outdoor insulators in cold climate regions. Copyright © 2004 John Wiley & Sons, Ltd.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.490

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 head0.032
GPT teacher head0.249
Teacher spread0.217 · 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

Citations14
Published2004
Admission routes3
Has abstractyes

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