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Record W4312123895 · doi:10.3390/app122412690

Effect of Raster Angle and Infill Pattern on the In-Plane and Edgewise Flexural Properties of Fused Filament Fabricated Acrylonitrile–Butadiene–Styrene

2022· article· en· W4312123895 on OpenAlexaff
Hamza Qayyum, Ghulam Hussain, Muhammad Sulaiman, Malik Hassan, Aaqib Ali, Riaz Muhammad, Hongyu Wei, Tauheed Shehbaz, Muhammad Aamir, Khurram Altaf

Bibliographic record

VenueApplied Sciences · 2022
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMaterials scienceFlexural strengthComposite materialRaster graphicsFlexural modulusAcrylonitrile butadiene styreneScanning electron microscopeGeometryMathematicsComputer science

Abstract

fetched live from OpenAlex

Fused Filament Fabrication (FFF) is a popular additive manufacturing process to produce printed polymer components, whereby their strength is highly dependent on the process parameters. The raster angle and infill pattern are two key process parameters and their effects on flexural properties need further research. Therefore, the present study aimed to print test specimens with varying raster angles and infill patterns to learn their influence on the in-plane and edgewise flexural properties of acrylonitrile–butadiene–styrene (ABS) material. The results revealed that the highest in-plane and edgewise flexural moduli were obtained when printing was performed at 0° raster angle. In comparison, the lowest values were obtained when the printing was executed with a 90° raster angle. Regarding the infill pattern, the tri-hexagon pattern showed the largest in-plane modulus, and the quarter-cubic pattern exhibited the greatest edgewise flexural modulus. However, considering both the modulus and load carrying capacity, the quarter-cubic pattern showed satisfactory performance in both planes. Furthermore, scanning electron microscopy was used to investigate the failure modes, i.e., raster rupture, delamination of successive layers and void formation. The failure occurred either due to one or a combination of these modes.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.228

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 head0.016
GPT teacher head0.202
Teacher spread0.186 · 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 teacher head, 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

Citations25
Published2022
Admission routes1
Has abstractyes

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