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Record W2016433065 · doi:10.1109/ias.2013.6682620

Circuit breaker transient recovery voltage requirements for medium voltage systems with NRG

2013· article· en· W2016433065 on OpenAlexaffabout
Rasheek Rifaat, Tarjit Singh Lally, James Hong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsJacobs (Canada)
Fundersnot available
KeywordsCircuit breakerEmtpTransient (computer programming)Transient recovery voltageReliability engineeringElectric power systemDistribution boardTransmission systemVoltageEngineeringComputer scienceElectrical engineeringPower (physics)Transmission (telecommunications)Voltage regulator

Abstract

fetched live from OpenAlex

The industrial distribution power systems in Northern Alberta supplies electrical energy to satellite locations and mining areas. In some aspects, these systems differ from their counterparts in regular utility distribution cases. Accordingly, they require special attention when performing transient recovery voltage (TRV) studies and identifying ratings for new breakers to be added to the system. Meanwhile, North American (IEEE) and European (IEC) Standards are embarking on significant efforts to harmonize breaker specifications and testing requirements including TRV tests. An Electro Magnetic Transient Program (EMTP) study has been performed to verify system TRV requirements under different conditions against Standard requirements and supplier's provided test data. Concerns, lessons learned and some other findings associated with the study are documented in the paper for future references and for advancing robust usage of EMTP (ATP) for the performance of such studies for sub-transmission and distribution systems in different electrical systems.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.211
Teacher spread0.196 · 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 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
Published2013
Admission routes2
Has abstractyes

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