Predicting Crack Instability Behaviour of Burst Tests from Small Specimens for Irradiated Zr-2.5Nb Pressure Tubes
Bibliographic record
Abstract
A scaling approach, based on the deformation J-integral at maximum load obtained from small specimens, is proposed for predicting the crack instability behaviour of burst tests on irradiated Zr-2.5Nb pressure tubes. An assessment of this approach is carried out by comparison with other toughness criteria such as the modified J-integral and the plastic work dissipation rate approach. The largest discrepancy between the different parameters occurs for materials of intermediate toughness which exhibit the most stable crack growth and tunnelling up to maximum load. A study of one material of intermediate toughness suggests crack-front tunnelling has a significant influence on the results obtained from the 17-mm-wide specimens. It is shown that for a tube of intermediate toughness the different approaches can significantly underpredict the extent of stable crack growth before instability in a burst test even after correcting for tunnelling. The usefulness of a scaling approach in reducing the discrepancy between the small- and large-scale specimen results for this material is demonstrated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".