Typical Zirconium Alloys Microstructures in Nuclear Components
Bibliographic record
Abstract
Abstract The different microstructures typically found in nuclear components made of zirconium alloys are discussed in this paper. These include material in a variety of thermo-mechanical conditions, e. g., cold rolled, stress relieved, recrystallized, welded, biphasic, together with minority second phases belonging to the original material or incorporated due to in-service conditions. The anisotropic crystalline structure of zirconium is exploited in microscopical observations by means of polarizer filters that enhance the contrast between different grains, and greatly aid the identification in most microstructures. Most microstructural variations across a wide range of length-scales, such as those produced by welding processes, can be effectively resolved by traditional optical microscopy (OM). However, some finer microstructures like those found in CANDU 1 (CANada Deuterium Uranium) reactor pressure tube material, or some minority second phase particles like the Zr(Fe, Cr) 2 precipitates in Zircaloy-4 cannot be completely resolved by this technique. Thus, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) are required in such cases. For SEM observations we show the valuable issue of the scale in specific microstructural studies, which allows quantifying microstructural parameters using image analysis. For TEM observations, we have greatly benefited from the electron diffraction diagrams, which have allowed us to investigate the crystalline structure of irradiated second phase particles, which would remain unnoticed to both, OM or SEM observations.
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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 | 0.000 |
| 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".