Creep and Creep-Rupture of Polymer Composite Laminates
Bibliographic record
Abstract
Creep and creep-rupture of uni-directional composite laminates were characterized and modelled. Individual and interactive influence of stress, temperature, moisture, and physical aging on creep and creep-rupture of a polymer composite (Hexcel F263 epoxy reinforced with 54% by volume of Toray T300 carbon fibers) were studied. The composite exhibited linear creep at constant stresses ≤ 7 MPa in the temperature range 295 – 503K. Moisture accelerated creep through plasticization (i.e. lower the Glass Transition Temperature, Tg) of the epoxy matrix and moisture-induced creep acceleration was found to be equal to creep acceleration in a dry sample by equivalent temperature increase. Moisture accelerated creep-rupture. Physical aging retarded creep and accelerated creep-rupture. In addition to reducing the moisture diffusivity and saturation moisture, physical aging caused a reduction in the magnitude of creep and creep-rupture acceleration by moisture when compared to non-aged material at the same moisture level. Similar interactive influence was observed at various stress and / or temperature levels. The data have been appropriately modelled and are currently being used in the modelling of creep and creep rupture of multi-directional laminates. The results of the modelling will be presented and discussed at the time of presentation.
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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".