Effect of loading rate, viscosity, and binder activation on the bending response of an infiltrated UD-NCF
Bibliographic record
Abstract
Assessing the bending response of infiltrated reinforcement fabrics is crucial in wet compression molding (WCM) as it affects macroscopic wrinkling. Binder-stabilized fabrics may be used in WCM to improve handleability and reduce defects, necessitating their characterization. This study examines the bending behavior of an infiltrated binder-stabilized carbon fiber unidirectional non-crimp fabric (UD-NCF), focusing on the effects of viscosity, loading rate, and binder pre-activation. Infiltration reduces bending stiffness compared to dry fabric owing to lubrication and lower tow-stitch friction, while higher loading rates increase bending stiffness for all considered conditions. Moreover, binder pre-activation increases fabric stiffness by enhancing tow-stitch cohesion and friction. As the first investigation on infiltrated binder-stabilized UD-NCF bending, this work advances understanding of the complex bending response.
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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 | 0.000 |
| 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 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".