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Record W2734781854 · doi:10.1049/iet-epa.2017.0244

Mutual inductance and magnetic force calculations between thick bitter circular coil of rectangular cross section with inverse radial current and filamentary circular coil with constant azimuthal current

2017· article· en· W2734781854 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

VenueIET Electric Power Applications · 2017
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsPolytechnique MontréalInterDigital (Canada)
Fundersnot available
KeywordsElectromagnetic coilInductanceCurrent (fluid)Constant (computer programming)PhysicsConstant currentAzimuthCross section (physics)InverseMechanicsNuclear magnetic resonanceOpticsGeometryMathematicsVoltageComputer science

Abstract

fetched live from OpenAlex

In many engineering applications, the coils of different geometrical shapes are used. Usually, these coils (circular, right etc.) are with the constant currents in different directions. In the literature, there are many papers on the calculations of the magnetic fields of the circular coils with the constant azimuthal currents or the calculations of the mutual inductance and the magnetic force between them. In some applications, where the high intensity magnetic fields are required the circular metal plates and insulating spacers are used with the inverse radial current. Such configurations form an electromagnet named after its inventor Bitter. In this study, the authors calculate the mutual inductance and the magnetic force between the thick Bitter coil of rectangular cross‐section with the inverse radial current and the circular filamentary coil with the constant azimuthal current. The semi‐analytical and the analytical expressions of these quantities are obtained over complete elliptic integrals of the first and second kind as well as Heuman's lambda function. There is one simple integral which has to be solved numerically. The results of this method are compared by those obtained by the modified filament method for the presented configuration. All results are in an excellent agreement.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
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
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.239
Teacher spread0.228 · 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