Thermal and thermo-mechanical aging of epoxy-mica insulated stator bars
Bibliographic record
Abstract
Operating generators just above their nameplate rating could enable power utilities to avoid buying high-cost electricity during peak demand and even ultimately to delay building new power plants. However, such increases can have a major impact on the temperature rise of the insulation system and might reduce its lifetime. The aim of this study is to evaluate the effects of temperature on the expected lifetime of power generators using an epoxy-mica insulation system. To evaluate aging of this insulation system in the laboratory, an experiment was designed to reproduce accelerated thermal and thermo-mechanical stresses. The 15 stator bars used in this experiment were thermally aged at three different constant temperatures. In addition, in order to simulate the stress caused by machine starts and stops, sequences of thermal cycling were inserted at specific times during the constant thermal aging. After each completed cycle, dissipation factor and partial discharge levels were measured in order to evaluate the degradation of the insulation system. Overall, the bars were aged for five complete cycles of 2 000 hours for a total of 10 000 hours, of which 75% was done under constant temperature and the rest under cycling. All the bars were subjected to a breakdown voltage test at the end of aging.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".