Mesoscopic Modeling of 3D Four-Directional Braided Composites
Bibliographic record
Abstract
3D four-directional braided composites are becoming widely used in the aeroengines due to their excellent transverse properties such as stiffness, strength, fracture toughness and damage resistance. In spite of great achievements in composite materials, the model of 3D four-directional braided composites gives rise to considerable challenge in establishing interior fiber bundle structure which is curved and twisted in jamming condition. Original circular cross-section of fiber bundle is squeezed into oval shape ellipse in manufacturing process of the jamming action. Thus, a novel mesoscopic modeling approach for 3D four-directional braided composites was proposed in this study, which considered the fiber bundle cross-section’s deformation. Firstly, an analytic equation to describe the transformation of fiber bundle cross-section was established based on the equal area of the ellipse and circle. Secondly, the parameters of this equation were achieved using the Matlab simulation. It was concluded that the compacted, non-interfered fiber bundle model constructed was in good agreement with actual structure. This paper provides the mathematical relationship between braiding parameters and geometric dimensions of unit cell model. Numerical results showed that the value of braiding pitch length has a relative calculation error less than 4% compared with test data. The modeling technique lays a foundation for further mesomechanics investigation on 3D four-directional braided composites.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".