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Record W4287846867 · doi:10.1109/eic51169.2022.9833208

Additive Manufactured Dielectrics for Aerospace Electrical Insulation Applications

2022· preprint· en· W4287846867 on OpenAlexaff
Christopher Severns, Sorin Dinculescu, Thierry Lebey

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsSafran Electronics (Canada)
Fundersnot available
KeywordsDielectricMaterials scienceStereolithographyComposite materialContext (archaeology)Dielectric strengthDielectric spectroscopyAerospaceAnisotropyDielectric lossOptoelectronicsOptics

Abstract

fetched live from OpenAlex

This paper investigates if there are inherent limitations with Additive Manufactured (AM) materials to preclude their use in electrical insulation applications, and if any anisotropic behavior exists with respect to print orientation. Two different AM processes, stereolithography (SLA) and selective laser sintering (SLS), were utilized to produce dielectric samples. Conductivity, Dielectric Relaxation Spectroscopy, bulk partial discharge, and dielectric breakdown tests were performed on samples printed in different orientations. Dielectric characterization was performed over a wide range of frequencies (DC to 1 MHz) and temperatures (-60C to +200C; material permitting). To help address the lack of meaningful electrical information in AM materials, this paper proposes a methodology for evaluation and dielectric quantification of basically "unknown" materials. Generally, the materials studied exhibited acceptable dielectric behavior but no clear advantages other than enabling complex multifunction designs (dielectric, structural and thermal). Dielectric strengths exceeding 30 kV/mm for a 1.0 mm thickness were exhibited in both SLA and SLS samples, with strength scaling laws explored over a range of thicknesses from 300 µm to 5.0 mm. For differing print orientations (XY-plane, YZ-pane, 30-degree inclined XY-plane) no discernible anisotropic dielectric behavior was observed. Motivations for the use of AM produced dielectrics in a civil aerospace context is also treated.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.248
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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