Bibliographic record
Abstract
A time efficient method for predicting ratchetting strain is proposed. By finding the ratchetting rate, at only a few cycles, the ratchetting strain of any cycle can be determined. It is shown that a trajectory of the origin of stress may be defined in the deviatoric stress space as the ratchetting progresses. The method for obtaining this trajectory from a standard uniaxial asymmetric cyclic loading is presented. At the beginning, this trajectory coincides with the initial stress origin and approaches the mean stress, displaying a power law relationship with the number of loading cycles. This path defines a moving frame of reference for stress tensor calculations. Ratchetting rates for different cyclic loading are calculated with the knowledge of this frame of reference and through utilizing a constitutive cyclic plasticity model which incorporates deviatoric stresses and back stresses that are measured with respect to this moving frame. The proposed model is used to predict ratchetting strain of 1070 steel under single step constant amplitude and multi-step loading. The method is also applied to non-proportional loading. Results obtained agree with the available experimental measurements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".