Probabilistic Analysis of the Fatigue Crack Growth Based on the Application of the Monte-Carlo Method to Unigrow Model
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Bibliographic record
Abstract
This paper presents results obtained from the combination of the UniGrow fatigue crack growth model with Monte-Carlo simulation method. Four sets of available statistical fatigue crack growth data were used for the analysis. The material resistance to the fatigue crack propagation was modelled as a random input parameter while the geometry and loading conditions were kept deterministic. The measure of comparison was chosen to be the distribution of the number of cycles required to propagate the crack from a certain initial to the desired deterministic size. The difference between the “within specimen” and “from specimen to specimen” variability is assessed. Influence of the former on fatigue crack growth predictions is demonstrated to be negligible. It is shown that the probability distributions obtained from the numerical analysis closely resemble distributions obtained from the available experimental data.
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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