Recycled Glass Fiber Composites from Wind Turbine Waste for 3D Printing Feedstock: Effects of Fiber Content and Interface on Mechanical Performance
Why this work is in the frame
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Bibliographic record
Abstract
This research validates the viability of a recycling and reusing process for end-of-life glass fiber reinforced wind turbine blades. Short glass fibers from scrap turbine blades are reclaimed and mixed with polylactic acid (PLA) through a double extrusion process to produce composite feedstock with recycled glass fibers for fused filament fabrication (FFF) 3D printing. Reinforced filaments with different fiber contents, as high as 25% by weight, are extruded and used to 3D print tensile specimens per ASTM D638-14. For 25 wt% reinforcement, the samples showed up to 74% increase in specific stiffness compared to pure PLA samples, while there was a reduction of 42% and 65% in specific tensile strength and failure strain, respectively. To capture the level of impregnation of the non-pyrolyzed recycled fibers and PLA, samples made from reinforced filaments with virgin and recycled fibers are fabricated and assessed in terms of mechanical properties and interface. For the composite specimens out of reinforced PLA with recycled glass fibers, it was found that the specific modulus and tensile strength are respectively 18% and 19% higher than those of samples reinforced with virgin glass fibers. The cause for this observation is mainly attributed to the fact that the surface of recycled fibers is partially covered with epoxy particles, a phenomenon that allows for favorable interactions between the molecules of PLA and epoxy, thus improving the interface bonding between the fibers and PLA.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it