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Record W1955026342 · doi:10.1109/ecce.2015.7309843

Development of mutual inductance formula for misaligned planar circular spiral coils

2015· article· en· W1955026342 on OpenAlexaff
Bryan Esteban, Nikola Stojakovic, M.A. Sid-Ahmed, Narayan C. Kar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsInductanceElectromagnetic coilPlanarSpiral (railway)Maximum power transfer theoremEquivalent series inductanceTopology (electrical circuits)Power (physics)PhysicsElectrical engineeringComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

The mutual inductance, M, is a key figure of merit in all magnetically coupled systems, but it plays an especially crucial role in the design of loosely coupled coils used in inductive power transfer (IPT) systems. This paper presents a new closed form expression for the mutual inductance of planar circular spiral coils also known as Archimedean coils. This new expression, which is derived using the magnetic vector potential, accounts for both coil-to-coil separation and axial misalignment distances. In what follows, the analytical formulation is first presented. Next, MATLAB is used to evaluate the resulting expression over a wide range of separation and misalignment distances and corresponding plots are obtained. Finally, a physical prototype is built, tested, and its measured mutual inductance is compared against the previously obtained analytical results.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.044
GPT teacher head0.241
Teacher spread0.197 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations22
Published2015
Admission routes1
Has abstractyes

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