An assessment of delayed hydride cracking initiation in PHWR pressure tubes using in-house ZIPTAS code
Bibliographic record
Abstract
The earlier fitness-for-service (FFS) evaluation of a service-induced volumetric flaw in the pressure tube of a Pressurized Heavy Water Reactor (PHWR) was based on the threshold peak stress that can lead to initiation of Delayed Hydride Cracking (DHC) as a function of number of reactor Heat-up/cool-down cycles. This design curve was a conservative lower bound to the limited test data available at that time. It, however, did not account for the effect of flaw geometry explicitly. To overcome this restriction, an improved flaw evaluation procedure that accounts for the stress relaxation due to hydride formation and decohesion process by a non-linear process zone lying at the tip of a blunt flaw was proposed by Scarth and Smith (2001). This model has been adopted by the Canadian Standards Association in their FFS code of practice. The process zone model is, however, tedious as it involves a set of non-linear equations that need to be solved simultaneously. In the present work, the process zone model is implemented in an in-house computational code (ZIPTAS) and a set of parametric studies are performed to assess the influence of flaw geometry, flaw size and service loads on the maximum nominal stress that will not lead to initiation of DHC from a volumetric flaw in a pressure tube. The developed ZIPTAS code is validated with several published results and is expected to be useful to both plant operators and regulators for quick and robust assessment of flaw size that can be safely permitted for continued operation of PHWRs.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".