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Record W2528668624 · doi:10.1109/tia.2017.2761824

Applying Arc-Resistant Technologies to Medium-Voltage Variable Frequency Drives

2017· article· en· W2528668624 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 Industry Applications · 2017
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsRockwell Automation (Canada)
Fundersnot available
KeywordsSwitchgearCircuit breakerEngineeringVoltageElectrical engineeringElectric arcArc (geometry)Automotive engineeringFault (geology)Mechanical engineeringElectrode

Abstract

fetched live from OpenAlex

Arc-resistant low/medium-voltage switchgear and motor controls continue to provide proven levels of additional personnel safety in most every petroleum and chemical facility. The IEEE and the International Electrotechnical Commission generated testing guides and standards for these products, which are open to some level of interpretation when applied to products other than traditional medium-voltage circuit breaker or fundamental motor controller structures for which the current available standards and guides were intended when they were initially written. All medium-voltage variable frequency drives, because of their inherent designs, require high volumes of cooling air, which pose a real challenge in regards to providing full arc-resistant capabilities and compliance to the present testing guides, procedures, and standards. This paper will deliver real solutions to this problem through the application of unique cooling processes, arc channeling technologies, structural enhancements, arc fault energy-limiting methodologies, and special application considerations when applying arc-resistant medium-voltage drives.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.983
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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