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Record W2118244405 · doi:10.1109/tdei.2002.1007710

Influence of post-manufacturing residual mechanical stress and crosslinking by-products on dielectric strength of HV extruded cables

2002· article· en· W2118244405 on OpenAlexaff
N. Amyot, Éric David, S.Y. Lee, I.H. Lee

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2002
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsÉcole de Technologie SupérieureHydro-Québec
Fundersnot available
KeywordsMaterials scienceComposite materialResidual stressDielectric strengthDielectricFourier transform infrared spectroscopyStress (linguistics)

Abstract

fetched live from OpenAlex

Residual mechanical stresses from manufacturing always exist in freshly extruded HV cables. These stresses are not uniformly distributed in the cable insulation bulk material. Five different HV cables were analyzed with respect to residual mechanical stresses and dielectric breakdown strength. Photoelastic measurements have been carried out and show that maximum residual stresses range from 4.5 to 6 MPa and are located near the conductor shield. Breakdown strength measurements with respect to mechanical stresses have also been performed up to, and above the maximum stresses observed. A significant decrease in ac breakdown strength was observed for stresses higher than 6 MPa. Typical crosslinking by-products from dicumyl peroxide (DCP) have been measured by FTIR spectroscopy at five radial positions in the insulation bulk. Measured by-products consisted in acetophenone and cumyl alcohol. FTIR measurements show that crosslinking by-products content is higher in the bulk of the insulation than near the conductor and insulation shields thus showing a diffusion process. Moreover, residual amount of cumyl alcohol is generally between 1 and 3 times that of acetophenone. No important effect of both by-products on the ac dielectric breakdown strength was observed.

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 categoriesMeta-epidemiology (narrow)
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 score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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.

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

Citations27
Published2002
Admission routes1
Has abstractyes

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