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Record W7116071776 · doi:10.82417/0gr9-xm05

Impact analysis on non-planar 3D-printed FFF parts

2025· other· en· W7116071776 on OpenAlexfundno aff

Bibliographic record

VenueEspace ÉTS (ETS) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCharpy impact testSlicingAnisotropyFused filament fabricationPlanarImpact resistanceLayer (electronics)

Abstract

fetched live from OpenAlex

This study investigates the Charpy impact resistance of non-planar 3D-printed parts manufactured by fused filament fabrication (FFF). Traditional planar slicing introduces anisotropy and layer delamination, leading to suboptimal mechanical properties. Non-planar slicing methods, such as sinusoidal and bell-shaped patterns, offer promising enhancements by optimizing layer alignment and stress distribution. Five sample variations were designed using FullControl GCode Designer and tested following ASTM D6110 standards. Results indicate a significant improvement in impact strength for vertically oriented non-planar specimens, with up to 50% greater resistance than planar counterparts, as well as reduced anisotropy when comparing horizontally and vertically fabricated parts. This work highlights the potential of non-planar slicing for reducing anisotropy and improving the structural integrity of FFF parts, offering insights for industrial applications requiring tougher 3D-printed 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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.061

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 head0.010
GPT teacher head0.288
Teacher spread0.279 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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