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Record W2909338288 · doi:10.2514/6.2019-1857

Stretchable Structure for a Benchtop-Scale Morphed Leading Edge Demonstration

2019· article· en· W2909338288 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIAA Scitech 2019 Forum · 2019
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsEnhanced Data Rates for GSM EvolutionScale (ratio)Computer scienceMaterials scienceArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Adaptive structures and morphing aircraft technologies have generated much interest in the aerospace community, including regular sessions at AIAA conferences. However, due to the lack of suitable materials to make stretchable structures with loadbearing ability, relatively few works address the development of morphing wings that undergo substantial area change despite the advantage of doing so for the aerodynamic performance. At SciTech 2018 we first presented an approach to development of a stretchable skin based on carbon nanotube-polyurethane sheets with approximately 25 wt.% carbon nanotubes. In this paper we describe the production and properties of the nanocomposite skin, a complimentary support structure produced via structural optimization and 3D printing, and integration of these components along with a custom-designed actuation mechanism within a 25 cm wide, 200 cm long benchtop-scale morphing leading edge demonstration.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.736

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 science0.0000.000
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 head0.004
GPT teacher head0.199
Teacher spread0.195 · 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