Thermal models for MTM45-1 and Cycom 5320 out-of-autoclave prepreg resins
Bibliographic record
Abstract
Out-of-autoclave prepregs require a two-step cure cycle. The first step is a low temperature cure to consolidate the laminate and build sufficient green strength to proceed to the second step, a free-standing post-cure at traditional autoclave temperatures to fully cross-link the resin. Process modeling can help design a robust cure cycle to avoid scrapping large parts in production. The focus of this article is to develop the cure kinetics, viscosity, and glass transition temperature models for two commercially available out-of-autoclave epoxy resins. Since the cure kinetics model is the basis for all other thermal models, the cure kinetics model was validated using a one-dimensional heat transfer analysis on thick prepreg laminates. Finally, the out-of-autoclave resin models were compared to a traditional autoclave resin system to highlight the difference in resin reactivity for out-of-autoclave processing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".