Experimental investigation on mechanical characterization of 3D printed PLA produced by fused deposition modeling (FDM)
Bibliographic record
Abstract
Abstract This study aims to systematically experimental investigate the influence of infill-patterns (IPs) on specific mechanical responses of parts fabricated by fused deposition modeling (FDM). A poly-lactic-acid (PLA) feedstock filament is utilized in the manufacturing process. Furthermore, six types of infill-patterns (deposition angle), namely full honeycomb, rectilinear, triangular, fast honeycomb, grid, and wiggle, are designed and printed. In order to determine the mechanical properties of manufactured parts, tensile tests are carried out. The mechanical properties such as extension, stress, elongation, energy, and Young’s modulus are considered as objective functions. As a result, there is a direct correlation between mechanical properties and infill patterns. Thus, it is essential to select the best infill-pattern in terms of their applications, giving sufficient strength without overdoing time and cost. Based on the results, a triangular infill-pattern has a maximum value of ultimate tensile strength and E-module (15.4 and 534 MPa, respectively). On the other hand, the wiggle pattern is more flexible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".