Development of Non-Destructive Condition Monitoring Techniques for Low-Voltage Cables
Bibliographic record
Abstract
Nuclear power plants contain more than one thousand kilometres of electrical cables. A large majority of these cables are dedicated to Instrumentation and Control (I&C) functions. I&C cables are key components of a nuclear power station because they link measuring and control equipment to the instrumentation used to monitor and control the plant. Research data and operational experience show that nuclear power plant cable materials gradually become brittle and may crack, thereby resulting in loss of dielectric strength and increased leakage current. The main stressors causing age-related degradation are elevated temperatures and ionising radiation. Most cables installed at the CANDU® stations were initially qualified for a 30-40 year service life. As station personnel now face the prospect of plant life extension, the focus is on assessing the remaining life of the cables (including Design Basis Event (DBE) survivability) beyond the 30-40 year period. The number of techniques available for on-site monitoring is limited because of the strong requirement from station personnel to use non-destructive and non-intrusive techniques. As a result, a CANDU Owners Group (COG) R&D project was initiated to develop new non-destructive and non-invasive techniques for on-site condition monitoring and help the station users assess the remaining life of installed cables. This paper summarizes the results obtained to date using three non-destructive techniques: the measurement of cable indentation and post-indentation parameters, the measurement of electrical dissipation factors at low frequencies, and the measurement of sound velocity using laser-ultrasound.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".