Probabilistic Safety Assessment for Instrumentation and Control Systems in Nuclear Power Plants: An Overview
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Deregulation in the electricity market has resulted in a number of challenges in the nuclear power industry. Nuclear power plants must find innovative ways to remain competitive by reducing operating costs without jeopardizing safety. Instrumentation and Control (I&C) systems not only play important roles in plant operation, but also in reducing the cost of power generation while maintaining and/or enhancing safety. Therefore, it is extremely important that I&C systems are managed efficiently and economically. With the increasing use of digital technologies, new methods are needed to solve problems associated with various aspects of digital I&C systems. Probabilistic Safety Assessment (PSA) has proved to be an effective method for safety analysis and risk-based decisions, even though challenges are still present. This paper provides an overview of PSA applications in three areas of digital I&C systems in nuclear power plants. These areas are Graded Quality Assurance, Surveillance Testing, and Instrumentation and Control System Design. In addition, PSA application in the regulation of nuclear power plants that adopt digital I&C systems is also investigated. KEYWORDS: probabilistic safety assessmentinstrumentation and control systemsgraded quality assurancerisk-informed regulationnuclear power plantspower system deregulationcommon cause failures
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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