An Investigation Into Low Velocity Impact Of 3D Printed Thermoplastic Plates
Bibliographic record
Abstract
PolyLactic Acid (PLA) is the most widely used material for 3D printing, especially in industrial applications. PLA is an environment-friendly material as it is biodegradable and has high stiffness and low cost. But PLA shows brittle nature when subjected to out-of-plane loading, i.e. impact. Hence, in this paper, a pendulum impact test apparatus was used to perform impact tests and understand the impact damage characteristics of 3D printed PLA coupons. A high-speed and an infra-red camera were used to investigate the impact damage characteristics of the coupons and understand the failure mechanisms. 24 coupons were printed on a Prusa i3 MK2S 3D printer with a 0° raster angle and different layer thickness. The layer thickness was varied from 0.10 mm to 0.18 mm and the coupons were impacted with 3 J impact energy at two different impact locations, which were, at the center and near the upper clamped edge. For impact at the center of the specimen, the absorbed energy first increased and then decreased and the coupons with higher absorbed energy showed more damage. The absorbed energy was always higher for the coupons impacted at the second location, i.e. near the clamped edge with an only exception in the case of 0.16 mm layer thickness. Coupons with 0.16 mm layer thickness had the highest absorbed energy percentage for the impact to the plate center, however for the impact near the clamped edge, 0.12 mm layer thickness had the highest absorbed energy percentage. Specimens with cracks in the direction perpendicular to the orientation absorb more energy than the specimens with cracks in the direction of extrudates. And specimens with only horizontal or vertical cracks absorb less energy than the coupons with cracks in multiple directions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".