Warpage investigation of carbon/PEEK discontinuous long fibre thin panels
Bibliographic record
Abstract
Discontinuous Long Fibre (DLF) composites, composed of randomly-oriented strands of chopped unidirectional pre-impregnated tape, have been used in the aerospace industry to produce intricate, net-shape parts with complex features – replacing complicated metallic brackets with single, lightweight parts. Carbon/PEEK DLF composites suffer from warpage problems driven by several factors including their high processing temperatures and semi-crystalline matrix shrinkage. This work aims to characterize warpage of thin-gauge parts and pursue mitigation. Results showed that the magnitude of warpage reduces with decreasing strand size and increasing thickness. At thicknesses greater than 2 mm, warpage appeared relatively stable. The introduction of ribbed features was explored as a mean of mitigating warpage by increasing part stiffness. No significant impact on the magnitude of warpage was observed within parts. However, the addition of ribs helped to control the warped shape of the part.
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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) | 0.002 | 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".