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Record W2125592459 · doi:10.1002/etep.1649

Power quality improvement in DC electric arc furnace plants utilizing multi-phase transformers

2012· article· en· W2125592459 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Transactions on Electrical Energy Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsnot available
Fundersnot available
KeywordsTransformerEngineeringElectrical engineeringSingle-phase electric powerElectric arc furnacePower qualityDistribution transformerThree-phaseElectric arcVoltageAutomotive engineeringPower factorElectronic engineeringMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Conventional feeding systems for DC electric arc furnace steel making plants usually include a 12-pulse rectifier that is fed by Δ/Δ and Δ/Y three-phase transformers. In this paper, with the use of the PSCAD/EMTDC software (Developed by Manitoba HVDC Research Center Inc., Canada), the advantages of applying multi-phase transformers for supplying such loads are evaluated and compared with the traditional three-phase power supply systems. A well-designed secondary winding for multi-phase transformer is proposed, and then the modeling of such transformers is discussed. With some proper power quality indices applied, it is shown that utilizing multi-phase transformers can lead to power quality improvement such as current/voltage harmonic reduction and unbalance mitigation. Copyright © 2012 John Wiley & Sons, Ltd.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
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
Bibliometrics0.0010.000
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 head0.038
GPT teacher head0.306
Teacher spread0.268 · 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