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Record W2183309402 · doi:10.1109/antem.2004.7860632

On the limits of validity of the impedance boundary conditions for the analysis of induced currents in solid conductors

2004· article· en· W2183309402 on OpenAlexaff
K. A. S. N. Jayasekera, I.R. Ciric

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInduction Heating and Inverter Technology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEddy currentElectrical conductorConductorElectrical impedanceSkin effectElectromagnetic shieldingBoundary value problemElectromagnetic fieldCurvatureMechanicsElectromagnetic inductionPhysicsAcousticsElectromagnetic coilMathematical analysisElectrical engineeringEngineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

The analysis of induced currents in conducting bodies due to the presence of an external magnetic field variable with time is necessary in numerous areas of applied electromagnetics, such as induction heating, eddy-current braking, electromagnetic shielding and electromagnetic levitation. An accurate study of the induced currents requires the field solution for both the inside and outside of the conductor. Exact analytical solutions are possible for a limited number of geometries. In order to reduce substantially the amount of computation, at high frequencies one can use the impedance boundary condition (IBC) models where only the field solution outside the conductor is needed. The simplest model is the perfect electrical conductor (PEC) model. More accurate results can be obtained by using the standard impedance boundary condition (SIBC) model and also the curvature corrected surface impedance models.

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)0.009
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.005
Scholarly communication0.0040.006
Open science0.0020.002
Research integrity0.0020.004
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 head0.071
GPT teacher head0.313
Teacher spread0.243 · 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 designSimulation or modeling
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

Citations5
Published2004
Admission routes1
Has abstractyes

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