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Record W4402639681 · doi:10.1177/00405175241269744

Design optimization of a three-dimensional hexagonal braiding technique

2024· article· en· W4402639681 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

VenueTextile Research Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversity of British Columbia
FundersNational Natural Science Foundation of China
KeywordsHexagonal crystal systemMaterials scienceEngineering drawingComputer scienceNanotechnologyEngineeringCrystallographyChemistry

Abstract

fetched live from OpenAlex

The three-dimensional hexagonal braiding technique, utilizing an individually controllable horn gear mechanism, enables the automatic generation of a wide range of intricate fabric preforms for structural composites. However, the limited yarn-carrying capacity and the potential risk of collisions between horn gears hinder the development of this type of braiding machine. This study proposes an optimized hexagonal braiding technique to enhance the machinery and control system, aiming to improve the yarn-carrying capacity and prevent collisions. Specifically, the optimization includes modifying the switch device, developing a new algorithm for controlling each horn gear, and designing a control panel to facilitate human–computer interaction. Additionally, simulations of various fabric structures demonstrate improved braiding capability compared to traditional hexagonal braiders. Moreover, a prototype braider is assembled, capable of automatically braiding diverse fabrics using the control system, thereby demonstrating its potential to manufacture complex composite preforms.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.094
GPT teacher head0.353
Teacher spread0.259 · 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