Void and porosity characterization of uncured and partially cured prepregs
Why this work is in the frame
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Bibliographic record
Abstract
Void characterization and porosity measurements of uncured and partially cured carbon/epoxy prepregs are challenging due to the soft nature of the matrix. If samples need to be cut from a larger laminate, the act of cutting and polishing can alter the void morphology. This paper presents a method to prepare samples for optical microscopy by infiltrating the pore space in the soft prepreg with a room-temperature curing low-viscosity resin to support the structure during cutting and polishing in preparation for optical microscopy. The methodology is validated by comparison with results obtained from porosity measurements using the ASTM D2734 standard density method. The paper also explores the use of thickness measurements to determine porosity. It is shown that thickness measurements can be used to estimate porosity for the no-bleed out-of-autoclave prepreg system used in the present study but that the accuracy is lower than using microscopy or density methods.
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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 | 0.000 | 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 | 0.000 | 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 it