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Record W7164171028 · doi:10.4050/f-0079-2023-1211

Automated Fiber Placement Double in-situ Manufacturing Technology of Thermoplastic Composites Components

2023· article· W7164171028 on OpenAlexaff
Marcin Głodzik, Radosław Wojtuszewski, Aleksander Banas, Konrad Farbaniec, Jarosław Sienicki, T. Gałaczyński, Wojciech Krauze

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsThermoplastic compositesComposite numberFiberProduction (economics)ThermoplasticAdvanced composite materials

Abstract

fetched live from OpenAlex

Presented idea describes the manufacturing approach to low-cost production and assembly of a composite part in one operation with the use of AFP (Automated Fiber Placement) technology. The proposal illustrates production of the floor panel dedicated to helicopters and airplanes. Traditionally, stiffeners are joined to the composite skin after it has been manufactured, most often in a different fixture, position, and other process. The present idea takes full advantage of the AFP method, which makes it possible these separate processes to be combined in one operation, allowing the hybridization of the fiber placement skins with the joining of the stiffeners. The article presents then design, tooling and manufacturing principals of a such innovative hybrid approach in a building of complex aircraft composite components.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.018
GPT teacher head0.252
Teacher spread0.233 · 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
Published2023
Admission routes1
Has abstractyes

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