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Record W2184438095 · doi:10.1109/ias.1988.25155

Analysis and design of a three-phase offline DC-DC converter with high frequency isolation

2003· article· en· W2184438095 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

VenueConference Record of the 1988 IEEE Industry Applications Society Annual Meeting · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsConvertersRectifier (neural networks)Duty cycleInverterPower (physics)VoltageThree-phaseElectronic engineeringComponent (thermodynamics)Network topologyPower semiconductor deviceElectrical engineeringComputer sciencePhase (matter)Topology (electrical circuits)High voltageEngineeringPhysics

Abstract

fetched live from OpenAlex

Single-phase offline switch-mode rectifiers (or, offline DC-DC converters) face severe component stresses in applications above 10 kW. This study shows that in three-phase switch-mode rectifier (SMR) topologies, component stresses are reduced and performances improved substantially. These improvements include faster response times, reduced switching stresses of the power semiconductor devices, and reduced size and rating of associated reactive components. The authors also present an analysis and design approach for three-phase SMR converters under large input-voltage and load variations. Output voltage control is achieved by varying the duty cycle of the inverter power semiconductor switches. The theoretical results are verified experimentally.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 categoriesnone
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 score0.881
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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