Effect of compaction roller on layup quality and defects formation in automated fiber placement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Application of automated fiber placement is limited by defects formed in the prepreg tows during the layup process. An extensive experimental study is performed to investigate the effect of compaction roller on the quality of the layup. Five different compaction rollers with different stiffness and architectures were manufactured and employed to dispense prepreg tows at various process conditions. Layup quality was examined and different defects including tow buckling and blister were identified. In addition to automated fiber placement trials, static testing and finite element simulations were performed to probe the pressure distribution and contact width of each roller. This data was used to support and understand the results of the automated fiber placement trials. Results indicate the solid elastomer rollers that are compliant enough to produce the same level of contact width under similar levels of compaction forces are superior to the perforated rollers in terms of achievable layup quality.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it