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Record W2141913243 · doi:10.1109/pesc.2004.1354725

Multiple frequency modeling of high frequency resonant inverter system

2004· article· en· W2141913243 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

Venue2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551) · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsInverterHarmonicsResonant inverterConvertersPower (physics)RLC circuitElectronic engineeringAC powerHarmonicHarmonic analysisComputer scienceControl theory (sociology)PhysicsElectrical engineeringEngineeringVoltageCapacitorAcousticsControl (management)

Abstract

fetched live from OpenAlex

Multiple-frequency modeling (MFM) offers a general small signal modeling methodology for resonant type converters. A DC/AC resonant inverter is decomposed into two pure DC sub-circuits for each harmonics, the excitations of which are orthogonal. However, such decomposition makes the definitions of active power P, reactive power Q, apparent power S and instantaneous power p difficult, while these concepts are important for resonant inverter system power flow analysis and controller design. We extend the MFM by giving general definitions of P, Q and S in terms of the state variables of the series of decomposed sub-circuits of MFM. We present a general circuit model for high frequency DC/AC resonant inverter system. With this model, power flow analysis can be conveniently performed. Performances are analyzed in detail for a high frequency inverter-ac bus system.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.642
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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