The effect of the percentage of steered plies on the bending-induced buckling performance of a variable stiffness composite cylinder
Bibliographic record
Abstract
Abstract The fiber steering capability of automated fiber placement machines offers the designers more room to fully exploit the directional properties of composite materials. Circumferential stiffness tailoring by fiber steering can considerably increase the bending-induced buckling performance of laminated composite cylinders. The potential structural improvement resulting from fiber steering depends on different design parameters such as the number of plies considered for fiber steering in a laminate. In this study, the buckling performance improvement of a variable stiffness (VS) composite cylinder is investigated for different percentages of plies considered for fiber steering in a multilayered composite laminate. A surrogate-based modeling along with a multi-step optimization is used in the design procedure of this study. The improvements in the buckling performance are shown and verified using finite element analysis in ABAQUS software. The mechanisms leading to buckling performance improvement of VS composites are also investigated and presented for different percentages of fiber-steered plies.
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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 | 0.001 |
| 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) | 0.001 | 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".