Electromagnetic Energy Coupling Mechanism on Cables and Systems - A Comparison Composite Aircraft Versus Metal Aircraft and Impact on Testing Procedure
Bibliographic record
Abstract
In the past ten years, the all composite commercial aircraft has become a reality and the need for the aircraft designer to consider electromagnetic threats has also grown. Aircraft systems are now designed with miniaturized electronic components, which make them more sensitive to EMI; and it turns out that the safety of flight relies on the functionality of some of these systems. Composite materials (Polymer Matrix Composites, PMCs) are characterized by their low conductivity that greatly reduces the shielding effectiveness of the aircraft structure and consequently the protection of systems against HIRF, and mainly against lightning indirect effects. Indeed, due to the low conductivity, lightning current which is focused in low frequency spectrum, will not decay through the composite skin material as quick as it does in all metal skin; and aircraft skin is not thick enough compared to the skin effect for this low frequency spectrum, to reduce substantially the current through composite structure. Therefore the diffusion effect of lightning current in composite aircraft structure will be substantially higher than all metal aircraft, so there will be the developed voltages in systems. On an all metal aircraft, the equipment is referenced to aircraft structure which is mainly resistive and keeps systems at the same potential. On a composite aircraft, this can only be achieved through a grounding network which impedance is governed by its resistance and self inductance. Consequentially, the coupling mechanism of electromagnetic fields and current on cables will not be equivalent for composite and all metal aircraft, nor their induced effects on systems, mainly for common mode ones. Thus the following question would be raised: For an equivalent electromagnetic threat coupling to cables interconnecting avionic systems, does the qualification per the present standards RTCA DO 160 (or equivalent) using a metallic bench test meet the expectations of tests for systems in composite aircraft? This paper gives an insight on the difference on coupling mechanisms that may lead to systems susceptibility, on the two types of aircraft.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".