Replacing stitching and weaving in natural fiber reinforcement manufacturing, part 1: mechanical behavior of unidirectional flax fiber composites
Bibliographic record
Abstract
This paper presents a novel natural fiber reinforcement manufacturing approach, based on a combination of short flax fibers and unidirectional flax yarns inspired by a papermaking process. The short fibers are used as a binder, replacing weaving and stitching used in textile-based reinforcements. The tensile and compressive properties of three different composites, in both longitudinal and transverse directions, were studied in order to highlight the effect of the mat binder. The presence of short fibers in the composite resulted in a slight decrease of about 10% of the longitudinal tensile modulus and strength. However, the transverse tensile properties are almost doubled. A similar trend was obtained in compression loading, where the addition of short fibers decreases the compressive modulus and strength. Particularly, the compressive strength in the yarn direction was more influenced by the presence of short fibers and was reduced by 30% compared to a decrease of 10% in the case of tensile loading. Here again, the transverse modulus was slightly increased, even if no effect was observed on the transverse compressive strength. The presence of the short fibers also shows a significant positive effect on the fracture behavior in tensile loading. The fractured surface is more uniform and presents a reduction of the splitting and crack formation along the unidirectional yarn direction.
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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".