On the Comparison of Hydroelectric Runner Fatigue Failure Risk Based on Site Measurements
Bibliographic record
Abstract
Abstract The fatigue reliability of a turbine runner is closely related to its dynamic behavior. Over the past few years, Hydro-Québec has performed measurement campaigns on many of its turbine runners. These measurements led to the evaluation of the fatigue risk level of each runner in various operating conditions, which allows operating conditions with a higher risk of crack propagation to be avoided. This paper presents the results for turbine dynamic behavior assessed in steady-state conditions. Stress levels at strain gauge locations are used to evaluate the risk of fatigue cracking based on the Kitagawa-Takahashi diagram. Results show a good correlation between the calculated risk of cracking and real cases of cracks found in runners. Furthermore, the results comparison highlights a apparent tendency for recent designs to be more prone to cracking at speed-no-load operating condition than older designs. The paper gives an overview of the methodology used and discusses the conclusions derived from the sample of turbine runners available for this study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 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".