MétaCan
Menu
Back to cohort
Record W4402764308 · doi:10.36602/ijeit.v7i2.180

Single Curvature Bending of Structural Stitched Textile Reinforcements Part I: Experimental Work

2024· article· en· W4402764308 on OpenAlexaboutno aff
Hafeth Bu Jldain

Bibliographic record

Venueالمجلة الدولية للعلوم الهندسية وتقنية المعلومات. · 2024
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsnot available
Fundersnot available
KeywordsBendingCurvatureTextileWork (physics)ReinforcementMaterials scienceComposite materialStructural engineeringEngineeringMechanical engineeringGeometryMathematics

Abstract

fetched live from OpenAlex

Aerospace structural components made from polymer matrix composites (PMCs) offer numerous advantages. Their high stiffness and high strength combined with low densities enable lower fuel consumption coupled with higher payloads. As a result, PMCs provide an important economic advantage over typical metallic airframes. Textile reinforcements for PMCs are made by assembling reinforcement fibres, typically carbon. Then, the textile reinforcements are typically cut into smaller pieces, stacked, draped and assembled into a dry assembly called a preform, the shape of which generally approaches that of the PMC part to be made. This manufacturing process is labour intensive and expensive.Novel thick, net-shape, drapable, high fibre volume fraction (vf) textile reinforcements used toward manufacturing aerospace PMCs are being developed at the University of Ottawa. The technology enables the manufacturing of flat, drapable multilayered near net-shape preforms. The bending and in-plane shear behaviours of such novel thick reinforcement textiles was investigated to understand and define the behaviour of such thick fabric reinforcements when formed into required shapes. A bending apparatus was developed for investigating the bending behaviour of these novel thick reinforcement fabrics.

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), Insufficient payload (model declined to judge)
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 score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.258
Teacher spread0.237 · 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 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueالمجلة الدولية للعلوم الهندسية وتقنية المعلومات.Same topicMechanical Behavior of CompositesFrench-language works237,207