Research on a fiber ring generating algorithm for manufacturing fiber composite rotating structures of complex geometry
Bibliographic record
Abstract
Due to its light weight and high strength, carbon fiber reinforcement resin based composite (CFRC) has been widely used in aerospace, military, and many other industries. As the manufacturing technology develops, the geometry of CFRC components has seen significant changes, such as closed surface from the traditional open surface, or quite sophisticated topologies from simple shapes. As a result, fabrication of CFRC is confronted with challenging issues related to the design of fiber placement trajectory for optimal performance. In this paper, a trajectory generating algorithm is proposed based on the centroid curve of a quasi-rotational structure, where the centroid curve is the connection of centroids of the cross-sections of the structure. After the centroid curve of the component is achieved, the cross-section profiles perpendicular to the centroid curve can be determined. An efficient number of profiles are identified to avoid any overlap among neighboring profiles along the centroid curve. In this manner, the essential data for ultimate trajectory design are eventually obtained that can precisely reflect placement angles. The present work will effectively enhance the accuracy of trajectory of fiber placement and promote the mechanical property of CFRC components.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".