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Record W4311187388 · doi:10.36227/techrxiv.21701348

Electromagnetic Characterization of Conductive Aircraft CFRP Composite for Lightning Strike Protection and EMI Shielding

2022· preprint· en· W4311187388 on OpenAlexaff
Richard Xian‐Ke Gao, Hui Min Lee, Wei-Bin Ewe, Siok Wei Tay, Jayven Chee Chuan Yeo, Warintorn Thitsartarn, Zaifeng Yang, Masoud Mahmoudi, Alexandre LeBrun, Edi Juanda, Johan Köhler, Wensong Wang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsComposite numberElectromagnetic shieldingEMILightning (connector)Electrical conductorMaterials scienceLightning strikeComposite materialTransmission lineShieldStructural engineeringElectromagnetic interferenceElectrical engineeringEngineeringLightning arresterGeology

Abstract

fetched live from OpenAlex

This paper presents the electromagnetic characterization of new carbon fiber reinforced polymer (CFRP) composite applied in aircraft for tackling the lightning direct effect and enhancing the electromagnetic shielding effectiveness. The CFRP composite design is deliberated for ameliorating the electrical conductivity of composite. With the aid of equivalent medium modeling, the inherent electromagnetic properties of CFRP composite have been investigated. The simulated results illustrate that the lightning strike protection (LSP) capability and the electromagnetic shielding behavior of the newly developed aircraft composite have been improved as compared to the original CFRP composite, and comparable to that with copper mesh as a protective layer on top. In addition to simulation, an artificial lightning experiment has been carried out in accordance with SAE ARP5416 by mimicking the natural lightning strike attachment and also the measurement of the shielding effectiveness of the proposed CFRP composite has been conducted by using electromagnetic waveguide transmission line method. The experiment data has validated the simulation results and demonstrated the feasibility of the proposed CFRP composite design.

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 score0.001
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)0.0010.000

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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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