Mechanical and thermal study of <scp>3D</scp> printing composite filaments from wind turbine waste
Bibliographic record
Abstract
Abstract The subject of composite waste from the wind turbine blades has become more serious and challenging. Inspired by the recent popularity of the 3D printing industry, this work presents a step‐by‐step recycling solution to manufacture fiber reinforced filaments for fused filament fabrication. Polylactic acid filaments reinforced with 3, 5, and 10 wt% recyclate content are manufactured and tested using thermogravimetric analysis (TGA), and micro computed tomography (μCT). TGA results elucidate that an increase in the recyclate content translates into a reduction in the mean fiber length. Visualizing μCT results, it is confirmed that fibers are predominantly aligned along the filament length. Tensile specimens per ASTM D636 standard are manufactured and tested with results showing an improvement of, respectively, 20% and 28% in the specific tensile strength and modulus compared with pure PLA samples. The mechanical performance of the newly introduced recycled parts is also assessed through a coherent set of theoretical models, where an excellent agreement between the experiments and predictions is observed.
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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 | 0.000 | 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".