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Record W2543735223 · doi:10.1109/iecon.2006.347508

Evaluation on basic resonant structures and voltage clamping techniques

2006· article· en· W2543735223 on OpenAlexaff
Mizhi Zhang, Timothy Little

Bibliographic record

VenueProceedings of the Annual Conference of the IEEE Industrial Electronics Society · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsDalhousie University
Fundersnot available
KeywordsClampingNetwork topologyTopology (electrical circuits)Insulated-gate bipolar transistorClamperVoltageElectronic engineeringPower (physics)Electrical engineeringComputer scienceMaterials scienceEngineeringPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

As the increasing demand of soft switching techniques in order to further increase the efficiency at high frequency operation. Resonant structure is becoming more and more important in reducing the switching loss. Due to the resonant characteristic, excessive voltage over the main switches will be the main problem in high power application. Under this consideration, resonant and voltage clamping DC link are demonstrated and compared in this paper at different power level. Moreover, switching and conducting characteristic of the different devices have large impact on selection of topology. Different behavior of IGBT at high di/dt will change the loss distribution through the various resonant topologies. At last, morphological chart is designed to gain a better understanding on topology composition and selection based on efficiency

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.239
Teacher spread0.213 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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