Bibliographic record
Abstract
This paper examines the concept of Grid resilience in the context of the North American electricity supply system and the role existing (Generation II) light water–cooled nuclear power plants (NPPs) play in enabling and enhancing Grid resilience. (Because of similarities in technology and plant design, it is likely that most of the discussion in the paper is also relevant to Generation III and Generation III+ light water NPP designs. The applicability of the analysis to Canadian CANDU and Russian VVER technology has not been assessed.) The paper asks and answers three compound questions: (1) what is Grid resilience, and what is a resilient Grid? (2) what is a resilient nuclear power plant (rNPP), and what are the basic functional requirements of rNPPs? and in light of the answers to these questions, (3) are today’s U.S. NPPs significant Grid resilience assets? The conclusion reached is that existing U.S. commercial NPPs are safe and efficient capacity, energy, and reliability assets and they have demonstrated some Grid resilience benefit during regional weather events. However, today’s NPPs do not deliver the Grid resilience benefits nuclear power can and should provide the nation. The author argues that nuclear power’s unique fuel security (an attribute that could allow NPPs to energize the Grid during extended periods in which fuel could not be delivered to other types of power plants) is a compelling reason to develop future rNPPs that would deliver strategic Grid resilience benefits in the face of evolving hazards and threats to the U.S. Grid.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".