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Record W2169905135 · doi:10.1109/intlec.1992.268420

A fixed frequency ZVS high power, PWM SMR converter with zero to rated load variation capability

2003· article· en· W2169905135 on OpenAlexaff
Gerry Moschopoulos, P.D. Ziogas, G. Joós

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsPulse-width modulationEMIConvertersTransformerElectromagnetic interferenceElectronic engineeringPower (physics)Computer scienceElectronic circuitElectrical engineeringPulse-frequency modulationRectifier (neural networks)SnubberVoltageControl theory (sociology)PhysicsEngineeringPulse (music)Control (management)CapacitorPulse-amplitude modulation

Abstract

fetched live from OpenAlex

Typical 6-12 kW switched-mode rectifier (SMR) converters operate at switching frequencies of about 40 kHz, employ FET switches, and utilize pulse width modulation (PWM) power control techniques. These operating conditions create a harsh PWM switching environment which makes the switching to conduction loss ratio approximately 3 to 1, and complicates the task of EMI suppression. A zero-voltage switching (ZVS) SMR high power circuit that improves overall converter efficiency by significantly reducing switching losses while moderately increasing conduction losses is presented. A feature of the proposed converter is that ZVS fixed frequency operation is possible, even with the primary of the transformer disconnected. The modes of circuit operation are presented and analyzed. The feasibility of the proposed converter is demonstrated with experimental results on a 7 kW prototype unit.>

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.004
GPT teacher head0.184
Teacher spread0.180 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2003
Admission routes1
Has abstractyes

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