A numerical method for elasto-plastic notch-root stress–strain analysis
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Bibliographic record
Abstract
In this article, a computational modeling method of the multiaxial stress–strain notch analysis has been developed to compute elasto-plastic notch-tip stress–strain responses using linear elastic finite element results of notched components. Application and validation of the multiaxial stress–strain notch analysis model were presented by comparing computed results of the model to the experimental data of SAE 1070 steel notched shaft subjected to several nonproportional load paths. Based on the comparison between the experimental and computed strain histories, the elasto-plastic stress–strain model predicted notch strains with reasonable accuracy using linear elastic finite element stress histories. The elasto-plastic stress–strain notch analysis model provides an efficient and simple analysis method preferable to expensive experimental component tests and more complex and time-consuming incremental nonlinear finite element analysis. The elasto-plastic stress–strain model can thus be employed to perform fatigue life and fatigue damage estimates associated with the local material deformation.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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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