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Record W2144852060 · doi:10.1109/tie.2007.892742

Series–Parallel Resonant Converter in Self-Sustained Oscillation Mode With the High-Frequency Transformer-Leakage-Inductance Effect: Analysis, Modeling, and Design

2007· article· en· W2144852060 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 Industrial Electronics Magazine · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsLeakage inductanceInductanceTransformerElectronic engineeringEquivalent series inductanceControl theory (sociology)Resonant converterComputer scienceElectronic circuitEngineeringVoltageElectrical engineering

Abstract

fetched live from OpenAlex

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> An accurate modeling of the series–parallel resonant converter operating in self-sustained oscillation mode including the overlap effects of the output rectifying stage due to the leakage inductance of the transformer is presented. This paper presents a systematic procedure to study the aforementioned effects on the converter dynamic and steady-state performance. Such information is critical in designing isolated high-frequency resonance-based voltage-regulator modules for powering future subvoltage very large scale integration circuits such as microprocessors. The extended describing function technique is used to extract the steady-state characteristics in order to get an optimum converter design. Averaging state-space techniques are employed to derive a small-signal model that can describe the converter dynamics accurately. Analytical and simulation results are given. Finally, a 1-kW experimental prototype is built to verify the validity of the proposed work. </para>

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)0.001
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 score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.228
Teacher spread0.215 · 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