Corrosion des tubes de générateurs de vapeur : effet du soufre et du plomb sur les mécanismes d'endommagement
Bibliographic record
Abstract
In order to control nuclear power plant shutdown times and the dose received, it is necessary to identify the effect of corrosion products and more particularly of pollutants on the degradation of steam generator (SG) tubes. The study aims to analyze the effect of lead and sulfur present in the secondary environment of pressurized water reactors (PWR) on the susceptibility to stress corrosion cracking (SCC) of the external skin of steam generator tubes made of nickel-based alloys (600 and 690). The work will focus on mini Reserve U-bends (RUB) from the PhD thesis work of Jihane Ben Mohamed (PhD thesis Mines Saint Etienne, October 2021). A complete study of the influence of the most detrimental pollutants (Pb and S based) on the degradation modes will be necessary by combining various characterization techniques. To make significant progress in understanding the degradation modes during the solicitation of the tubes, it is necessary to obtain relevant data at the scale of the study, which can range from micrometer to nanometer. Fine analysis techniques using transmission electron microscopy (TEM) combined with energy dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS) will allow detection, localization and quantification of contaminants in the oxide layer and at the oxide/metal interface along the cracks of the SCC. The study of the passivity of these alloys as well as their intergranular oxidation in the presence of pollutants requires a metallurgical approach as well as microscopic characterizations at different scales. These different data will make it possible to propose a physicochemical model of the effect of lead and sulfur on the damage mechanism. Alloy 800 specimens, from the work of CNL (Canadian Nuclear Laboratory), will also be characterized for comparison and will allow the proposed model to be compared.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".