Development of Techniques for Composite Parts Failure Analysis in Static and Fatigue Mode - Application on Thermoset and Thermoplastic Materials for Rotorcraft Main Rotor Hub Analysis
Bibliographic record
Abstract
A model defined at the ply scale to predict the failure of laminated composites for static or fatigue loading is proposed. The model describes the loss of strength in the fiber direction for a significant level of transverse damage. This meso-scale model has been characterized on woven ply laminates used for rotorcraft dynamic components, such as glass/epoxy of Starflex®, carbon fiber/epoxy, and carbon fiber/PEEK of H160 main rotor hub. Failure behavior prediction at coupon level has been validated regarding static and fatigue failure mode in tension for epoxy resin woven ply laminates. Characterizations have been also provided for PEEK resin in balanced woven ply laminate, regarding static or fatigue failure mode. Those activities are crucial to increase the level of confidence in failure model, to rely on virtual testing at coupons level, and to better predict damage and failure at component level. This work intends to support the building block approach during development and certification of such critical applications for rotorcraft.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".