Investigation of intra-ply shear behavior of out-of-autoclave carbon/epoxy prepreg
Bibliographic record
Abstract
The successful formation of composite parts without defects remains a challenging issue due to the complexity of the forming process. A better understanding of the factors that cause these flaws is necessary to optimize the operation. The present work investigates the in-plane shear behavior of out-of-autoclave carbon epoxy thermoset prepregs OOA and its effect on wrinkling using the picture frame test. The deformability of OOA at the real processing conditions helps to understand the applicability of such material for forming processes such as the double-diaphragm forming technique with aims to minimize overall manufacturing time and cost. Tests were performed at varying temperatures and displacement rates in order to determine their contribution to the fabric deformability. Digital image correlation was used to take sequential images at various stages of deformation and capture the onset of wrinkling. It was found that the processing temperature (resin viscosity), displacement rate, and layer counts (layer interactions) are the three most important parameters that influence the wrinkling. Presence of resin between the layers makes them interact with each other and therefore has an impact on the each layer shear angle. These parameters were then analyzed using the Taguchi and analysis of variance techniques to determine which factor has the most significant influence on the wrinkling.
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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) | 0.001 | 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".