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Record W4387581368 · doi:10.3390/machines11100950

Correlation between Infill Percentages, Layer Width, and Mechanical Properties in Fused Deposition Modelling of Poly-Lactic Acid 3D Printing

2023· article· en· W4387581368 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

VenueMachines · 2023
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsFused deposition modelingPolylactic acidMaterials science3D printingUltimate tensile strengthComposite materialInfillDeposition (geology)Surface roughnessSurface finishModulusPolymerStructural engineeringEngineeringGeology

Abstract

fetched live from OpenAlex

The field of additive manufacturing (AM) has seen a transformation in the production of intricate and complex parts for various applications. Fused Deposition Modelling (FDM), among AM techniques, has garnered significant attention, particularly in fields like fibre-reinforced composites (FRC). In this study, the world of FDM-printed Polylactic Acid (PLA) components is explored, with a focus on how mechanical properties are influenced by infill percentages and layer widths. Through the utilisation of Response Surface Methodology (RSM), the optimisation of FDM-PLA 3D printing for a wide range of biomaterial applications is achieved, along with the unveiling of the potential for remarkable improvements in mechanical performance. Notably, a remarkable 91% reduction in surface roughness for PLA composites was achieved, accompanied by an impressive 25.6% and 34.1% enhancement in the tensile strength and Young’s modulus of fibre-reinforced PLA composites, respectively. This work, positioned at the crossroads of FDM, lays the groundwork for substantial advancements in the realm of 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.444

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 head0.037
GPT teacher head0.231
Teacher spread0.193 · 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