A Statistical Methodology for Determination of Safety Systems Actuation Setpoints Based on Extreme Value Statistics
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Bibliographic record
Abstract
This paper provides a novel and robust methodology for determination of nuclear reactor trip setpoints which accounts for uncertainties in input parameters and models, as well as accounting for the variations in operating states that periodically occur. Further it demonstrates that in performing best estimate and uncertainty calculations, it is critical to consider the impact of all fuel channels and instrumentation in the integration of these uncertainties in setpoint determination. This methodology is based on the concept of a true trip setpoint, which is the reactor setpoint that would be required in an ideal situation where all key inputs and plant responses were known, such that during the accident sequence a reactor shutdown will occur which just prevents the acceptance criteria from being exceeded. Since this true value cannot be established, the uncertainties in plant simulations and plant measurements as well as operational variations which lead to time changes in the true value of initial conditions must be considered. This paper presents the general concept used to determine the actuation setpoints considering the uncertainties and changes in initial conditions, and allowing for safety systems instrumentation redundancy. The results demonstrate unique statistical behavior with respect to both fuel and instrumentation uncertainties which has not previously been investigated.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it