The Effects of Thermally Induced Residual Stress on the Fatigue Behaviour of Fibre Metal Laminates
Bibliographic record
Abstract
The focus of this study is the examination and modification of existing analytical models for the calculation of effective stress intensity factor range and prediction of fatigue crack growth rates in GLass REinforced (GLARE) fibre metal laminates (FMLs). The effects of tensile residual stress have been largely unconsidered by existing models and therefore a modified model for calculating effective stress intensity factor range as well as crack propagation rate has been proposed. This modification includes the detrimental tensile residual stresses induced in the aluminum layers as a result of the laminate curing process. A previous model developed with the implementation of the fibre bridging mechanism has also been modified to include residual stress. The results of the analysis agree well with the trends and magnitudes found in the literature, though due to a lack of available experimental data, a direct evaluation of the proposed modifications was not possible.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".