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Record W4200314722 · doi:10.3390/en15010167

Pre-Breakdown and Breakdown Behavior of Synthetic and Natural Ester Liquids under AC Stress

2021· article· en· W4200314722 on OpenAlexaff
Beki Sékongo, Stephan Brettschneider, U. Mohan Rao, I. Fofana, M. Jabbari, Patrick Picher, Z. Yeo

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsHydro-QuébecUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsCurvatureMineral oilMechanicsElectric fieldVoltageBreakdown voltageMaterials scienceElectrical breakdownStreamer dischargeThermalDielectric strengthTransformer oilRADIUSComposite materialTransformerDielectricElectrical engineeringThermodynamicsPhysicsOptoelectronicsEngineeringMetallurgy

Abstract

fetched live from OpenAlex

In the last decades, a large focus is being placed on the sustainability and safety of the power transformer spectrum. Ester liquids, which have interesting properties such as high fire point and biodegradability, are gaining needed attraction. Since in-service condition, thermal aging deteriorates the physicochemical and electrical properties of liquid dielectrics, it is important to study their long-term behavior. In this contribution, the pre-breakdown and breakdown behavior of ester fluids (synthetic and natural) under AC stress are investigated. Important characteristics, such as partial discharge pre-inception voltage, partial discharge inception voltage, breakdown voltage, average streamer velocity, and inception electric field, were assessed. The influence of the radius of curvature (of high voltage needle electrode) as well as the thermal degradation of typical ester liquids are also discussed. Mineral oil was also included in the tests loop as a benchmark for comparative purposes. It is found that the pre-inception voltage of ester liquids was, in most cases, higher than that of mineral oil. For a given radius of curvature, the streamer inception and breakdown voltages decreased with thermal aging. During the streamer initiation, the electric field at the electrode tip decreased with the increase in the radius of curvature. The velocity of the streamers seems to increase with the decrease in the radius of curvature. The period of vulnerability, the so-called “delay time”, seems to be independent of the aging or the radius of curvature for a given condition of the liquid.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.365

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 head0.004
GPT teacher head0.205
Teacher spread0.201 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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