Compressive Mesoscale Damage Modeling of Continuous Fiber-Reinforced Flax Laminates
Bibliographic record
Abstract
Flax fibers have been observed to have specific mechanical properties on par with E-Glass. However, lack of knowledge on their mechanical behaviour as well as the absence of practical modeling tools have impeded the flax fiber from being used in structural applications. In this thesis, compressive mechanical testing was performed Flax/Epoxy laminates in order to capture and quantify the flax composite’s non-linear behaviour with emphasis on damage and plasticity evolutions. A continuum damage mechanics-based on the standard Mesoscale Damage Theory (MDM) developed previously by Ladeveze and LeDantec was developed to include compressive damage and plasticity evolutions. The model parameters were derived from experimental data and optimized using open-source algorithms. Validations have been performed on Flax/Epoxy and EGlass/Polyester laminate composites in compression, as well as E-glass/Epoxy in tension. The model successfully predicts the composite’s mechanical behaviour, and offers a robust predictive tool capable of aiding engineers and designers in the development of load-bearing natural fiber composites.
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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 | 0.001 | 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".