Novel Approach to Life Extension of Components in BWR
Bibliographic record
Abstract
Abstract The fundamental understanding and practical application for mitigating degradation of structural materials in boiling water reactor (BWR) is described. Controlling the electrochemical property of surface alters the electrochemical corrosion potential (ECP) of structural materials and subsequently affects the stress corrosion cracking susceptibility in high temperature water. It is evident that the presence of noble metals on the oxide surface dramatically improves the catalytic recombination efficiency of hydrogen (H2) to oxygen (O2) and hydrogen peroxide (H2O2) to form water (H2O), and thus results in a thermodynamically lowest ECP value when a stoichiometric or higher amount of hydrogen is present in the water. It is also observed that an protective insulating coating (PIC) layer created with powders of yttria-stabilized zirconia (YSZ), pure zirconium (Zr) or zirconium alloys by thermal spray, chemical vapor deposition (CVD), or physical vapor deposition (PVD) restricts the oxidant transport rate to the metal surface, and decreases the ECP in high temperature water containing high concentration of oxidants without addition or presence of H2. In addition, the longer lifetime of the ECP sensor was achieved by applying the thermal spraying coating with YSZ powders. Furthermore, surface treatment of the hard friction surface of steam line plug grips with a Ta2O5 coating improves the corrosion resistance of hard-friction coated aluminum steam line plug grips.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".