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Record W2976200201 · doi:10.1109/temc.2019.2940158

TM Shielding Effectiveness of Slotted Carbon Fiber Reinforced Polymer-Based Cylindrical Shell

2019· article· en· W2976200201 on OpenAlexafffund
Kai Wang, Jean‐Jacques Laurin, Ke Wu

Bibliographic record

VenueIEEE Transactions on Electromagnetic Compatibility · 2019
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectromagnetic shieldingTransverse planeMaterials scienceShell (structure)Boundary value problemComposite materialBoundary (topology)ConductivityTransverse magneticPolymerStructural engineeringPhysicsEngineeringMathematics

Abstract

fetched live from OpenAlex

The TM shielding effectiveness (SE) analyses of slotted carbon fiber reinforced polymer (CFRP)-based shells are presented in this letter. The multifilament doublet current method (MFDCM) is deployed to simulate the scattered and penetrated fields in the considered situation. The inner and outer regions of a slotted shell are separated by a hybrid boundary, which contains the material and slot parts. The material part is constituted of multilayered CFRP materials, whereas the slot part is a virtual boundary. A tensorial boundary condition (TBC) is then constructed to stand for the slotted shell with a chain matrix. The MFDCM is subsequently formulated by employing the TBC to estimate the EM performances of interests. Different slot angles of the shell and conductivity of the CFRP material are considered in our numerical calculations. Only transverse magnetic (TM) case is considered herein, yet the transverse electric (TE) situation can be handled straightforwardly with a similar formulation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 communication0.0000.000
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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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 designBench or experimental
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

Citations5
Published2019
Admission routes2
Has abstractyes

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Same venueIEEE Transactions on Electromagnetic CompatibilitySame topicElectromagnetic Compatibility and MeasurementsFrench-language works237,207