Bibliographic record
Abstract
Article C-6000 of Appendix C of ASME Section XI includes Z-factor load multipliers for straight pipes with circumferential flaws. Application of this article is limited to straight pipes with nominal pipe size (NPS) larger than 4 and materials with fracture toughness JIc higher than 105 kJ/m2. Section XI of the ASME B&PV Code does not provide Z-factors for pipes with axial flaws, even for pipes with NPS≥4. Feeders are small diameter pipes (NPS≤2.5) used in a primary heat transport system in the CANDU nuclear reactors. Developments of Z-factor load multipliers for warm-bent feeder bends with axial flaws under pressure are presented in this paper. An empirical approach was adopted using experimental results from the Feeder Bend Testing Program founded by the CANDU Owners Group. The elastic-plastic fracture mechanics stress has been defined by failure stress from the experiments. Limit load solutions for elbow/bends recently published by Kim et al. were discussed. Additionally, lower bound limit load simulations were performed using finite element models implemented for ANSYS. The results from straight pipe models exhibited good correlation with analytical solution. Numerical simulations for elbows/bends showed analogous trends for limit load of elbow/bends with axial cracks as reported by Kim et al.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".