Shakedown/Ratcheting Boundary Determination Using Iterative Linear Elastic Schemes
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a robust non-cyclic method to identify the boundary between the shakedown and ratcheting domains (ratchet boundary) directly without the need for cyclic analysis. The solution can be obtained using only linear-elastic FEA. The method is based on lower bound formulation in shakedown theory, which is safe for design. It offers an attractive alternative to cyclic elastic-plastic analysis since it is simple, and requires considerably less computational effort and computer storage space. Another attractive feature is that the method provides a go/no go criterion for the ratchet boundary, whereas the results of a cyclic elastic-plastic analysis are often difficult to interpret near the ratchet boundary. The proposed method is applied to a number of configurations that include two-dimensional and three-dimensional effects.
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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