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Analysis of Shipboard Power Systems with Saturable Models of Synchronous Machines

2025· article· W4417250265 on OpenAlexaff
Shadman Saqlain Rahman, Abhay Kaushik, Fardin Sohel, Seyyedmilad Ebrahimi, Juri Jatskevich

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHarmonicsPropulsionElectric power systemSynchronous motorRobustness (evolution)Electromagnetic coilField coilPower (physics)Transient (computer programming)Electrically powered spacecraft propulsion

Abstract

fetched live from OpenAlex

Synchronous machines are widely utilized in modern shipboard power systems, serving as primary power generators and propulsion motors due to their reliability and efficient energy conversion. The propulsion motors are typically driven using variable-frequency drives (VFDs), which at megawatt power levels may be realized by thyristor-based AC–AC cycloconverters due to their robustness and high-power handling capability. However, cycloconverters introduce significant harmonics that degrade onboard power quality. Magnetic saturation in synchronous machines (which is often ignored by linear models) impacts the machine’s impedance characteristics and also changes the field winding excitation level required to maintain the AC bus voltages at the desired level. To capture both effects, the electromagnetic transient (EMT) simulations require accurate, yet computationally efficient, synchronous machine models. This paper proposes the use of a full-order saturable synchronous machine model for the analysis of the system harmonics and the field winding losses. The studies are conducted on a representative shipboard power system, and the advantages of using the proposed saturable model are demonstrated.

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)
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 score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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