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Record W2119742377 · doi:10.1109/tpwrd.2002.803717

No-load losses in transformer under overexcitation/inrush-current conditions: tests and a new model

2002· article· en· W2119742377 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 Power Delivery · 2002
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsInrush currentTransformerHarmonicsEmtpControl theory (sociology)EngineeringMechanicsVoltagePhysicsElectrical engineeringElectric power systemComputer sciencePower (physics)

Abstract

fetched live from OpenAlex

Tests were conducted on several transformers rated at 100 kVA or less and on a power transformer rated 370 MVA in an effort to characterize the no-load losses and magnetizing resistance for transformers subjected to overexcitation and inrush current. Analysis of the results revealed that the magnetizing resistance changes as a function of the peak magnetization flux or the amplitude of the magnetic field. A new model of the instantaneous magnetizing resistance (IMR) as a function of the instantaneous flux has been developed and its dynamic use in the Electromagnetic Transients Program (EMTP) allows the form of the hysteresis cycle and the mean losses in overexcitation to be reproduced with a high degree of accuracy. The same model also accounts for losses due to the harmonics superimposed on the fundamental. The results showed that the IMR calculated under inrush current conditions is higher than that in overexcitation conditions.

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 categoriesInsufficient payload (model declined to judge)
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 score0.997

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)0.0040.001

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 head0.041
GPT teacher head0.259
Teacher spread0.218 · 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