Multi-Variable Engineering Model for Axial Delayed Hydride Cracking Growth Rate in Pre-Irradiated Zr-2.5%Nb
Bibliographic record
Abstract
The growth rate of postulated delayed hydride cracks in CANDU Zr-2.5%Nb pressure tubes is an important material property required for flaw evaluations and leak-before-break assessments. It is monitored using surveillance pressure tubes according to the requirements of the Canadian Standards Association (CSA) Standard N285.4 [1]. Radial growth rate and axial growth rate are used to calculate the propagation of delayed hydride cracks in the through-wall direction and along the pressure tube length, respectively. The axial delayed hydride cracking growth rate had been previously found to increase exponentially with inverse absolute test temperature. This dependence had been described by an Arrhenius-type regression model with one explanatory variable. As more experimental results were obtained from surveillance pressure tubes, it has become possible to assess whether there may be statistically significant effects of other variables, which should be incorporated into the representative relation for the axial delayed hydride cracking growth rate. In this paper, multi-variable regression analysis has been used to develop an improved representative model for the axial delayed hydride cracking growth rate of irradiated Zr-2.5%Nb pressure tube material. The developed model explains approximately 93% of overall observed variation in the experimental data, and therefore has better predictive capabilities than the reference regression model with test temperature as a sole predictor. The developed multi-variable model is proposed to be incorporated into the scheduled revision (2010 edition) of the CSA Standard N285.8 as the representative predictive model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".