Fatigue life assessment of steel samples under various multiaxial loading spectra by means of Smith‐Watson‐Topper type damage descriptions
Bibliographic record
Abstract
Abstract Fatigue damage and life of SS304, S45C, and SNCM630 steel samples tested at various irregular axial‐torsional loading spectra were evaluated by means of 7 Smith‐Watson‐Topper (SWT) type damage descriptions. The overall damage was calculated over peak‐valley events of counted cycles by means of the product of stress and strain corresponding to the areas within stress‐strain hysteresis loops. Fatigue lives of 304 steel samples predicted by the SWT, Lorenzo‐Laird, Szolwinski‐Farris, and Chen‐Xu‐Huang models were found noticeably larger than those of experimentally obtained at various loading spectra. Predicted lives by these descriptions were found moderately in agreement with experimental data of S45C and SNCM630 steel samples. The predicted lives of steel samples by Socie, Lv et al, and the one presented in this study were closely agreed with experimental data due to their different descriptions. The modified SWT model further included the product of maximum shear stress and shear strain amplitude and related the overall damage to fatigue life through Coffin‐Manson equation. The choice of model descriptions for damage assessment was discussed based on their terms, areas underneath of hysteresis loops, and material damage mechanism.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".