Fault Tree Analysis for an Inspection Robot in a Nuclear Power Plant
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
The life extension of current nuclear reactors has led to an increasing demand on inspection and maintenance of critical reactor components that are too expensive to replace. To reduce the exposure dosage to workers, robotics have become an attractive alternative as a preventative safety tool in nuclear power plants. It is crucial to understand the reliability of these robots in order to increase the veracity and confidence of their results. This study presents the Fault Tree (FT) analysis to a coolant outlet piper snake-arm inspection robot in a nuclear power plant. Fault trees were constructed for a qualitative analysis to determine the reliability of the robot. Insight on the applicability of fault tree methods for inspection robotics in the nuclear industry is gained through this investigation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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