Radiation Aging of Cable Insulation Systems to Support Extension of Cable Electrical Assessment Techniques - CRADA 562 (Final Report)
Bibliographic record
Abstract
Radiation aging (primarily gamma radiation) affects a small subset of the LV cable population based on a 40-year operation. Increasing plant operating life to 60 or 80 years will result in additional cables experiencing degradation, either from radiation or from combined thermal and radiation effects. Previous research work done by EPRI and other researchers focuses on electrical diagnostics of thermal effects. However, the electrical diagnostic response of the cable system to radiation aging is minimally understood. In order to study the electrical responses from XLPE and EPR cabling and correlate these responses with radiation dose and level of thermal exposure, gamma radiation testing was performed at Pacific Northwest National Laboratory (PNNL). This report covers the radiation testing performed at PNNL, which involved irradiation of 30-foot long cables and short witness samples. The cabling was irradiated, at room temperature, using cobalt-60 gamma-rays to intervals of 10 million rads (10 Mrads), for a maximum of 70 Mrads. The results can be used to determine cable conditions (extent of damage) more accurately and localize where the degradation exists along the length of the cable (axial location). These insights can provide operators with the options to focus repair, mitigation, or replacement efforts locally.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".