Development of a metamodel to predict the transient and dynamic structural behaviour of a hydraulic turbine
Bibliographic record
Abstract
Abstract The present work deals with the construction of a simulation-based simplified model to provide stress of a hydraulic turbine during transient operation by leveraging two well-known concepts: hydraulic similarity and linear load combination. Because it combines multiple reduced order models, it is therefore called a metamodel. This strategy is applied to a 200 MW medium head Francis turbine which underwent an experimental campaign to acquire steady and transient stress signature. A modal analysis is first required to extract mode shapes, characteristics and corresponding stress tensors. Then a coarse CFD database is generated to populate the operating space. Modal forces are obtained through FEA for the gravitational, centrifugal and pressure loads. Modes are then combined using either quasistatic or dynamic assumptions. The model can provide in real-time most of the high amplitude stress occurring during transients and has a very good correspondence in operation.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".