Fracture Protection of CANDU Zr-2.5Nb Pressure Tubes With High Hydrogen Equivalent Concentration
Bibliographic record
Abstract
The core of a CANDU®1 (CANada Deuterium Uranium) pressurized heavy water reactor includes horizontal Zr-2.5Nb alloy pressure tubes that contain the fuel. Pressure-temperature limits are used in CANDU® reactors for normal operation heat-up and cool-down conditions to maintain margins against fracture. The pressure-temperature limits are determined by postulating a 20 mm long axial through-wall crack in the pressure tube and using a fracture toughness-based calculation procedure. Due to a corrosion reaction with the heavy water coolant, pressure tubes absorb deuterium isotope in service, resulting in an increase in hydrogen equivalent concentration. Experiments have shown that high hydrogen equivalent concentration reduces the fracture toughness of pressure tube material at low temperatures during reactor heat-up and cool-down from normal operating temperatures. New fracture toughness curves that are applicable to material with high hydrogen equivalent concentration have been developed to address this issue. These curves are being used to develop new pressure-temperature limits for fracture protection of CANDU® pressure tubes. The methodology for deriving the pressure-temperature limits for a CANDU® Zr-2.5Nb pressure tube using the new fracture toughness curves is presented in this paper. Preliminary results of pressure-temperature limits for a CANDU® reactor are also provided.
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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) | 0.000 | 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 | 0.001 | 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".