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Record W2798050947 · doi:10.1108/rpj-03-2017-0043

Additive manufacturing of shape memory polymers: effects of print orientation and infill percentage on mechanical properties

2018· article· en· W2798050947 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRapid Prototyping Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsInfillMaterials scienceExtrusionComposite materialShape-memory polymerUltimate tensile strength3D printingFused deposition modelingPolymerElastic modulusLayer (electronics)Shape-memory alloyStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Purpose Material extrusion additive manufacturing, also known as fused deposition modeling, is a manufacturing technique in which objects are built by depositing molten materials layer-by-layer through a nozzle. The use and application of this technique has risen dramatically over the past decade. This paper aims to first, report on the production and characterization of a shape memory polymer material filament that was manufactured to print shape memory polymer objects using material extrusion additive manufacturing. Additionally, it aims to investigate and outline the effects of major printing parameters, such as print orientation and infill percentage, on the elastic and mechanical properties of printed shape memory polymer samples. Design/methodology/approach Infill percentage was tested at three levels, 50, 75 and 100 per cent, while print orientation was tested at four different angles with respect to the longitudinal axis of the specimens at 0°, 30°, 60° and 90°. The properties examined were elastic modulus, ultimate tensile strength and maximum strain. Findings Results showed that print angle and infill percentage do have a significant impact on the manufactured test samples. Originality/value Findings can significantly influence the tailored design and manufacturing of smart structures using shape memory polymer and material extrusion additive manufacturing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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