Links between surface morphology changes and damage in a toughened epoxy adhesive
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the increased use of toughened epoxy adhesives in current transportation lightweighting efforts, it is critical that damage mechanisms, such as strain whitening, are understood and quantified. Damage quantification is needed for the constitutive models used in structural design; however, thin bond lines in adhesive joints limit direct observation. In this study, microscope observations of bulk toughened epoxy adhesive specimens subjected to tensile loading were linked to damage. Cracks on the surface opened during loading, leading to strain whitening at the crack tips and the initiation and propagation of shear bands. The stresses approximated at the crack tips suggested that particle cavitation could be occurring in these regions. Changes in specimen stiffness were linked to crack growth and the formation of shear bands. Material damage calculated using traditional load-unload stiffness (D ~ 35%) was higher than other methods such as change in material strength (D ~ 18%) and damage from changes in stiffness during load-reload (D ~ 19%). The differences were attributed to short-term viscoelastic effects. A new approach calculated damage from the strain whitening on the free surface (D ~ 21%). Values were in agreement with damage figures from other methods. The technique can quantify damage over the loading history and identify areas of damage localization.
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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 | 0.001 |
| 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