Bibliographic record
Abstract
A site-specific probabilistic seismic hazard analysis (PSHA) was performed in 2011 for the Bruce B Nuclear Generating Station site in Ontario, Canada (AMEC, 2011).The generated site-specific mean uniform hazard response spectra (UHRS) with an annual frequency of exceedance of 1E-4 at the top of the sedimentary rock has significant energy content in the high frequency range, as shown in Figure 1.This latest site-specific seismic hazard is considered for the Bruce B seismic probabilistic risk assessment (PRA).A Motor Control Center (MCC) located at EL. 601 feet in the Bruce B Reactor Building was selected for this study among other safety-related equipment, and its functional capacity was evaluated by means of the Conservative Deterministic Failure Margin (CDFM) method outlined in EPRI NP-6041-SL (1991).Once the High Confidence of Low Probability of Failure (HCLPF) capacity of the MCC is calculated, the median capacity is computed by assuming a conservative variability to determine the seismic fragility.For the purpose of comparison, the same MCC is evaluated using the Fragility Analysis (FA) method in accordance with EPRI TR-103959 (1994), including updates in EPRI 1019200 (2009) with a further probabilistic simulation implemented on the UHRS seismic demand.With these best estimate UHRS seismic demands, the HCLPF capacity of the MCC is improved 11% for function during and 18% for function after the earthquake.Comparisons of the two seismic fragility curves are given for function after the earthquake, in the conclusion.Figure 1.2011 UHRS vs. DBE Horizontal Free-Field Surface Response Spectra (5% Damping) 0 0.05 0.1 0.15 0.2 0.1 1 10 100 Spectral Acceleration (g) Frequency (Hz)Design Basis Earthquake
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.078 | 0.020 |
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".