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Record W4282927932 · doi:10.31276/vjste.64(2).34-41

V.I.E.T.N.A.M. by 4D printing of composites

2022· article· en· W4282927932 on OpenAlexaff
Suong V. Hoa, Daniel Rosca

Bibliographic record

VenueMinistry of Science and Technology Vietnam · 2022
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsComposite materialEpoxyMaterials scienceAnisotropyCuring (chemistry)Fused deposition modelingComposite numberEngineering drawing3D printingComputer scienceEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

This paper presents an application of 4D printing of composites (4DPC) to make composite structures of complex geometries without the need for complex moulds. This application is illustrated through the formations of the letters V, i, e, t, n, a, and m, which form the word Vietnam. In the procedure, laminates made of carbon/epoxy prepregs are laid on a flat mould. The deposition of the prepregs on the flat mould is done using an automated fibre placement machine (AFP), which can be considered as a large size 3D printer. For a smaller structure, the prepreg deposition can be accomplished using an AFP machine or by hand lay-up. Upon curing and cooling to room temperature, the laminate transforms itself from a flat configuration to the shape of the intended letter, except for the letter V. The mechanism that enables this transformation relies on the anisotropy of the laminate. This method has many potential applications, particularly in the delivery of bulky three-dimensional structures to remote locations.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0380.024

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMinistry of Science and Technology VietnamSame topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207