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Record W4311635227 · doi:10.6000/1929-5995.2022.11.07

A Simplified Analytical Solution for the Computation of Machine Path in Filament Winding of Cylindrical Angle-Ply and Double-Double Structures

2022· article· en· W4311635227 on OpenAlexvenueno aff
Artem Andrianov, A.P.F. Militão

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2022
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsnot available
Fundersnot available
KeywordsMandrelFilament windingComputationMaterials sciencePath (computing)GeodesicRotation (mathematics)Structural engineeringProtein filamentComputer scienceGeometryComposite materialEngineeringAlgorithmMathematics

Abstract

fetched live from OpenAlex

This paper presents a simplified computation approach for the machine path (or winding trajectory) of grid structures and tubes with a circular cross-section and angle-ply or double-double layup. The solution for the machine path is given through controllable degrees of freedom of a low-cost two-axis filament winding machine (FWM): mandrel rotation and translation of the delivery eye along the axis of the mandrel. The efficiency of the analytical solution for the machine path of the FWM was ascertained by automated laying the cotton thread over the geodesic and non-geodesic groove imprinted on the surface of a cylindrical polylactide mandrel. These results validated the possibility of manufacturing cylindrical composite structures with an angle-ply layup or double-double stacking sequence, without the need for expensive software, making the winding technology accessible to society and promoting university extension.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.103
GPT teacher head0.422
Teacher spread0.320 · 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 designSimulation or modeling
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

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