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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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, 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".