Impact of startup scheme on Francis runner life expectancy
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
Francis runners are subject to complex dynamic forces which might lead to eventual blade cracking and the need for corrective measure. Damage due to cracks in runner blades are usually not a safety issues but might generate unexpected down time and high repair cost. Avoiding the main damaging operating conditions is often the only option left to plant operators to maximize the life expectancy of their runner. The startup scheme is one of the available parameter which is controlled by the end user and could be used to minimize the damage induced to the runner. In this study, two startup schemes have been used to investigate life expectancy of Francis runner using in situ measurements. The results obtained show that the induced damage during the startup event could be significantly reduced with change to the startup scheme. In our opinion, an optimization of the startup scheme with regard to fatigue damage could extend significantly the life expectancy and the reliability of Francis runner.
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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 | 0.001 |
| 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 it