Interlaminar prestressing reinforcement of epoxy/glass fiber composites
Bibliographic record
Abstract
Abstract This paper describes an innovative through-thickness fiber reinforcement technology that employs in situ shrinking fibers to provide supplemental strength-enhancing interlaminar prestresses for fiber-reinforced polymeric laminate structures. Interlaminar stitched fibers shrink and provide prestress. The shrinkage is heat-activated and timed to coincide with epoxy-curing steps. This new technology includes the design and fabrication of in situ shrinking fibers to improve the peel strength of epoxy/glass fiber composite layers. The epoxy specimens were shrink-reinforced under four different conditions; the fibers were activated when the epoxy matrix was cured for 4, 12, and 20 h, or without having any curing time beforehand. Then, the peel strengths and flexural strengths were compared. Also, in-plane tensile tests were conducted under identical conditions to investigate whether the through-thickness shrinking fibers affect the in-plane properties. The results indicated that the maximum improvement from the fiber activation was shown when the epoxy was cured for 4 h, while there was no significant effect from the in-plane tensile test.
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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 | 0.000 | 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".