Revenue Requirements Method for Assessing the Cost Impact of Fuel Cladding Corrosion in a Supercritical Water-Cooled Small Modular Reactor: A Methodological Review on Life Cycle Costing Corrosion
Bibliographic record
Abstract
Abstract Canadian Nuclear Laboratories (CNL) is collaborating in the Joint European Canadian Chinese Development of Small Modular Reactor Technology (ECC-SMART) project to understand the corrosion behavior of the most promising candidate materials for a future supercritical water-cooled – small modular reactor (SCW-SMR). To support this aim and the project's requirements, the present study develops a costing method for assessing the impact of corrosion in a power generation cost model. This cost model builds on a methodological study of various corrosion engineering economics topics in nuclear power generation, such as the expected fuel cladding corrosion phenomena in a supercritical water-cooled reactor (SCWR) concept and estimating the main corrosion costs categories. This understanding is incorporated in a power generation cost model that applies the revenue requirements approach to life cycle costing (LCC). The LCC includes the main corrosion cost categories and a reliability factor used in assessing power generation costs, the costing of chemical species for controlling corrosion, and the present worth of revenue requirements. The method and model, therefore, provide a framework for understanding the kind of information available and needed for taking economical preventative corrosion measures for the current generation of water-cooled reactors and advanced reactors, such as the SCWR.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".