Comparison of Seismic Qualification Challenges for Nuclear Power Plants in North America and Peninsular India
Bibliographic record
Abstract
The seismic design basis for the Nuclear Power Plants (NPPs) in the United States is prescribed in United States Nuclear Regulatory Commission (USNRC) Regulatory Guide 1.60.The generic seismic design basis response spectrum for the NPPs in Canada is given in the Canadian nuclear standard CSA N289.3.Both these spectra are based on the strong motion earthquake records from the west coast of the North American continent.The Uniform Hazard Response Spectrum (UHRS), required for the Seismic Probabilistic Risk Assessment (SPRA) of a typical relatively older east coast plant (built more than three decades ago) is based on the east coast records and is quite different from its design basis.The differences between the east and the west coast spectra and the methodology of obtaining the structural response for the former on the basis of the latter have been reported in the literature.On the other side of the world, India is emerging as a major player in nuclear power generation.Although the Indian sub-continent and North America are situated on diametrically opposite sides of the globe, there are some striking similarities between the challenges related to the seismic qualification of NPPs situated in the Eastern North America (ENA) and Peninsular India (PI).The lessons learned in ENA can be effectively utilized in order to establish the seismic design and evaluation criteria of NPPs in PI.This paper compares the similarities and differences between the challenges on seismic qualification of structures, systems and components in NPPs situated on two diametrically opposite geographic locations.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".