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Record W1979318861 · doi:10.1109/tdei.2013.004018

Investigation into the eroding dry-band arcing of filled silicone rubber under DC using wavelet-based multiresolution analysis

2014· article· en· W1979318861 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2014
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsThermogravimetric analysisSilicone rubberElectric arcMaterials scienceComposite materialWaveletSiliconeAnalytical Chemistry (journal)ElectrodeChemistryChemical engineeringEngineering

Abstract

fetched live from OpenAlex

This paper describes an investigation into the dry-band arcing mechanism leading to erosion of filled silicone rubber in the DC inclined plane test. Good correlation is obtained between the formation of surface residue, hotspots and the eroding dry-band arcing. The hotspots detected by infrared camera correlates well with the temperature of degradation determined by thermogravimetric analysis and differential scanning calorimetry. To characterize the physical mechanism of dry-band arcing, wavelet-based multiresolution analysis up to seven levels of resolution is applied to the leakage current waveforms. The analysis shows that both stable and intense discharges characterize the eroding dry-band arcing. A time-to-eroding parameter is proposed to determine the relative resistance to the formation of residue. Faster accumulation of residue is evident under -DC than +DC. Earlier inception of erosion is obtained for the silica filled- as compared to the alumina tri-hydrate filled- silicone, in which the release of the water of hydration is postulated to suppress the residue formation.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
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 head0.028
GPT teacher head0.251
Teacher spread0.223 · 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