Dynamic Behavior of Fused Filament Fabricated Continuous Ramie Fiber‐Reinforced Polypropylene Composites under Diverse Loading Conditions
Bibliographic record
Abstract
The combination of continuous natural fibers and polypropylene enables the fabrication of environmentally friendly composites with recyclability, light weight, and high strength. Additionally, fused filament fabrication (FFF) 3D printing offers reliable process for efficient customized manufacturing of fiber‐reinforced composites. Therefore, this study fabricates continuous ramie fiber‐reinforced polypropylene (CRFRPP) composites through the FFF technique. Considering that composites are sensitive to various external conditions such as temperature, loading direction, and loading rate, this work investigates the mechanical behaviors of CRFRPP under a wide range of temperatures and strain rates when loaded parallel and perpendicular to the fiber orientation. The results indicate that the compressive strength of 3D‐printed CRFRPP under loading in the parallel fiber direction is higher than that in the perpendicular one. The maximum compressive strength is observed to be 176 MPa at a temperature of −40 °C and a strain rate of 2600 s−1, when loaded in the parallel fiber direction. Under dynamic loading, CRFRPP presents brittle behavior at lower temperatures (−40 and −10 °C) and softening behavior after yielding at higher temperatures (20 and 50 °C). Moreover, the CRFRPP exhibits different failure mechanisms that varied considerably depending on the imposed test conditions.
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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".