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Record W3036825419

Modeling of High Voltage Pollution Discharge to Investigate Hot Stick Flashover

2013· article· en· W3036825419 on OpenAlexaboutno aff
Dean Reske

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental sciencePollutionArc flashVoltageMaterials scienceElectrical engineeringEngineeringBiology
DOInot available

Abstract

fetched live from OpenAlex

Electric “flashover” or insulation breakdown has occurred on “hot stick” safety tools used on live AC transmission lines at Manitoba Hydro in 1997 and 2002. Investigations showed pollution flashover as the cause, whereby leakage currents cascade into flashover. Prior to reinstating live-line work with mitigation procedures, DC voltage experiments suggested an atypical flashover uncharacteristic of pollution flashover without leakage currents, which may require a different mitigation strategy. In this thesis, statistical analysis shows that relative humidity has a greater correlation than voltage with the type of flashover. Labeled a “fast flashover”, it seems to be distinct from pollution flashover, although not statistically significant. A time-stepping computer model was developed to calculate a critical voltage for flashover as a function of relative humidity. However, lack of data prevents the model from making firm conclusions. A list of recommended research is proposed to remedy these deficiencies to allow future model refinement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.192
Teacher spread0.176 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2013
Admission routes1
Has abstractyes

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