Bibliographic record
Abstract
The ASME B&PV Code provides design by analysis rules that address failure mechanisms under cyclic loading. One of these potential failure mechanisms is incremental plastic collapse, or ratcheting. Miller presented the technical basis for the present Code requirements in a technical paper in 1959. Miller’s equations for the ratchet boundary address a beam under a cyclic through-thickness thermal gradient acting together with a steady axial mechanical load. This ratchet boundary applies approximately to a pressurized cylinder with through-thickness thermal bending stress. Conditions arise sometimes in practice where cooling or heating is applied simultaneously to the inner and outer surface of pressure boundary. The extreme case of such a scenario arises when both surfaces experience the same thermal condition such that there is a cyclic thermal stress but both zero membrane thermal stress and zero thermal bending stress The question is, could ratcheting occur in this case? This paper derives the ratchet boundary for cases when the maximum temperature occurs mid-way through the thickness. The linearized stress due to thermal loading is zero. The solution is obtained using FE analysis and the Non-Cyclic Method (NCM) that has been proposed previously by the authors. The NCM is a generalization of the static shakedown theorem and allows the ratchet boundary to be calculated for both elastic and elastic-plastic cyclic stress states.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".