Accelerated Zero-Stress Hydrothermal Aging of Dry E-Glass Fibers and Service Life Prediction Using Arrhenius Model
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Bibliographic record
Abstract
Comprehending the degradation of glass fibers is crucial for service applications involving dry and wet conditions, especially when prolonged contact with water above room temperature is present. Depending on the polymer material, both thermosetting and thermoplastic matrices can permit the ingress of moisture. Therefore, fiber reinforcements embedded in the polymer matrix may experience moisture exposure. Additionally, some structural applications use fiber devoid of any matrix (dry fibers), in which water exposure must be avoided. In all of these cases, moisture may, therefore, have a significant impact on the reinforcing elements and the rate of degradation. The present work focuses on the effects of hydrothermal aging on the mechanical durability of long E-glass fibers by immersion in water at 60 °C, 71 °C, and 82 °C. A service life forecast model was created utilizing the Arrhenius technique, and a master curve of strength variation with exposure time was created for E-glass fibers at 60 °C. Using this modeling approach, it is possible to approximate the amount of time it will take to attain a given degradation level over a specified range of temperatures. Scanning electron microscopy was used to evaluate morphological changes in fiber surfaces due to hydrothermal exposure, while Fourier transform infrared spectroscopy and mass dissolution studies were used to elucidate the mechanism of the strength loss.
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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