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Record W2108942608 · doi:10.1109/elinsl.1994.401442

Influence of mechanical strain and stress on the electrical performance of XLPE cable insulation

2002· article· en· W2108942608 on OpenAlexaff
Éric David, J.-L. Parpal, J.‐P. Crine

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsMaterials scienceComposite materialUltimate tensile strengthStress relaxationViscoelasticityStress (linguistics)Strain (injury)Compression (physics)Creep

Abstract

fetched live from OpenAlex

XLPE insulation used in high-voltage cables is not only subjected to electrical stress but also to mechanical strains, either from internal residual strains created during manufacturing or externally applied when the cable is bent sharply. Due to thermally activated viscoelastic motion in the polymeric material, the original mechanical stress responsible for the strain may be completely or partly relaxed, with the permanent strain remaining unchanged. It is generally accepted that mechanical strain has a strong influence on the structural integrity and electrical performance of polymeric insulating materials. However, the influence of mechanical strain on the life and performance of insulating materials has still to be fully ascertained, since it depends on the nature (compression or tensile) and the direction of the strain and the magnitude of the remaining (unrelaxed) mechanical stress. In this paper, long-term and short-term breakdown tests were conducted on XLPE ribbon samples. To isolate the effect of the strain, a series of samples was drawn at different drawing ratios; the drawing rate and temperature allowed a situation of near-total stress relaxation. Results are presented for samples subjected to simultaneous tensile mechanical and electrical stress.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 score0.268
Threshold uncertainty score0.669

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)0.0010.000

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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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

Citations19
Published2002
Admission routes1
Has abstractyes

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