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Record W2152349236 · doi:10.1109/ias.1990.152261

A variable frequency soft commutated voltage source inverter delivering sinusoidal waveforms

2002· article· en· W2152349236 on OpenAlexaff
A. Chériti, Kamal Al‐Haddad, Louis‐A. Dessaint, D. Mukhedkar, V. Rajagopalan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversité du Québec à Trois-RivièresÉcole de Technologie SupérieureUniversité de MontréalPolytechnique Montréal
Fundersnot available
KeywordsPulse-width modulationInverterConvertersWaveformResonant inverterVoltageModulation (music)Computer scienceControl theory (sociology)Electronic engineeringEngineeringElectrical engineeringPhysicsControl (management)Acoustics

Abstract

fetched live from OpenAlex

A comparison of the rugged soft commutated pulse width modulation inverter (RSCPI) and the soft switched resonant pole inverter (SSRPI) is presented. These two converters have been introduced as alternatives to the resonant DC link inverter (RDCLI) and they are intended for use in variable speed drives. Based on the zero-voltage switching technique, both converters can operate at high switching frequency. A well-known pulse width modulation (PWM) strategy is adopted for the RSCPI. The performance results are compared with those obtained from the SSRPI using adaptive hysteresis control. This control is especially effective for- reducing conduction losses. It is shown that the RSCPI has reliability due to its inherent overload protection, but the SSRPI configuration is more practical in the sense that it reduces the losses and increases the system efficiency.< <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.

How this classification was reachedexpand

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.168
Teacher spread0.159 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
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

Citations8
Published2002
Admission routes1
Has abstractyes

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