MétaCan
Menu
Back to cohort
Record W4295953234 · doi:10.4050/f-0078-2022-1127

Development of a 3D Braided Preform for Rotorcraft Flex-beam

2022· article· en· W4295953234 on OpenAlexaff
Christopher Pastore, Dave Jann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsMaterials scienceComposite materialEpoxyYarnBundleBeam (structure)ReinforcementFiberDamage toleranceComposite numberStructural engineeringEngineering

Abstract

fetched live from OpenAlex

A novel 3-dimensional braiding concept, 4StepPlus, suitable for rotorcraft components where high damage tolerance and fatigue cycles are critical is explored in this paper. 3D textiles such as woven and braided fabrics provide through the thickness reinforcement and thus improved interlaminar strength properties over laminated composites. However, there are challenges in creating shapes with varying cross-sectional shapes and areas. A 4StepPlus 3D braiding approach is used to fabricate a subscale flexbeam with substantial changes in cross-section throughout the length of the part. The mechanical properties of 3D braided composites employing IM7 carbon and S2-glass with RTM epoxy are investigated. The effects of fiber bundle sizes is also assessed as it plays an important role in the performance as well as manufacturing of the component. The results indicate no significant effects of yarn size on the performance of the composites.

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 score0.003

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 head0.021
GPT teacher head0.241
Teacher spread0.219 · 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

Explore more

Same topicMechanical Behavior of CompositesFrench-language works237,207