Exploratory Analysis to Estimate Axial Fracture Toughness for Zr-2.5Nb Pressure Tubes Using Test Data From Small Curved Compact Specimens
Bibliographic record
Abstract
Zr-2.5Nb pressure tubes are in-core, primary coolant containment of CANDU(1) nuclear reactors. Technical requirements for in-service evaluation of pressure tubes are provided in the Canadian Standards Associate (CSA) N285.8. These requirements include the evaluation of service conditions for protection against fracture of operating pressure tubes and demonstration of leak-before-break. Axial fracture toughness for pressure tubes is a key input in the evaluation of fracture protection and leak-before-break. The 2015 Edition of CSA N285.8 provides a pressure tube axial fracture toughness prediction model that is applicable to pressure tubes late life conditions. The fracture toughness prediction model in CSA N285.8-15 is based on rising pressure burst tests performed on pressure tube sections with axial cracks under simulated pressure tube late life conditions. Due to the associated high cost of testing and high consumption of pressure tube material, it is not practical to perform a large number of fracture toughness burst tests. On the other hand, more fracture toughness data is required to improve the existing pressure tube axial fracture toughness prediction model. There is strong motivation to estimate pressure tube axial fracture toughness using test data from small specimens. The estimated pressure tube fracture toughness using test data from small specimens can fill the gaps in the burst test toughness data, as well as provide information on material variability and data scatter. Against this background, an exploratory analysis of estimating pressure tube axial fracture toughness using test data from small curved compact specimens has been performed and is described in this paper. The estimated values of pressure tube axial fracture toughness using the test data from small curved compact specimens are compared with the measured toughness from burst tests of pressure tube sections with axial cracks to check the feasibility of this approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".