Bibliographic record
Abstract
Abstract The crack growth resistance of irradiated Zr-2.5Nb pressure tubes is controlled by the initiation of voids and their subsequent growth and coalescence. The presence of particles that contribute to void nucleation is determined by the operating conditions/history of the pressure tube and by the concentration of pre-existing species, which is a function of the manufacturing process. The susceptibility of the pressure tubes to void nucleation is determined by the number and distribution of particles, the deformation properties of the matrix, and the stress state at the crack tip. The effect of irradiation on zirconium material is to increase the yield stress but to reduce the work hardening ability of the matrix and to promote strain localization, which, in turn, leads to void nucleation. Void nucleation is also enhanced by high values of stress triaxiality at or near the crack tip. For irradiated pressure tube material, both small-scale curved compact tension specimens and large-scale burst test sections are used to characterize the crack growth resistance. However, the measured fracture toughness can depend on the specimen geometry due to differences in constraint. The present investigation uses three-dimensional finite element analyses to characterize stress triaxiality at the crack tip in these different specimen geometries. Results of the numerical analyses are compared to the experimental evidence that provide qualitative evidence of differences in stress triaxiality at the crack tip for different specimen geometries.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".