Analysis of Variable Amplitude Fatigue Data of the P355NL1 Steel Using the Effective Strain Damage Model
Bibliographic record
Abstract
This paper proposes an analysis of variable amplitude fatigue data obtained for the P355NL1 steel, using a strain-based cumulative damage model. The fatigue data consist of constant and variable amplitude block loading, which was applied to both smooth and notched specimens, previously published by the authors. The strain-based cumulative damage model, which has been proposed by D.L. DuQuesnay, is based on the growth and closure mechanisms of microcracks. It incorporates a parameter termed net effective strain range, which is a function of the microcrack closure behavior and inherent ability to resist fatigue damage. A simplified version of the model is considered, which assumes crack closure at the lowest level for the entire spectrum and does not account for varying crack opening stresses. In general, the model produces conservative predictions within an accuracy range of two on lives, for both smooth and notched geometries, demonstrating the robustness of the model.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".