Numerical Study of the Winter-Kennedy Method—A Sensitivity Analysis
Bibliographic record
Abstract
The Winter-Kennedy (WK) method is commonly used in relative discharge measurement and to quantify efficiency step-up in hydropower refurbishment projects. The method utilizes the differential pressure between two taps located at a radial section of a spiral case, which is related to the discharge with the help of a coefficient and an exponent. Nearly a century old and widely used, the method has shown some discrepancies when the same coefficient is used after a plant upgrade. The reasons are often attributed to local flow changes. To study the change in flow behavior and its impact on the coefficient, a numerical model of a semi-spiral case (SC) has been developed and the numerical results are compared with experimental results. The simulations of the SC have been performed with different inlet boundary conditions. Comparison between an analytical formulation with the computational fluid dynamics (CFD) results shows that the flow inside an SC is highly three-dimensional (3D). The magnitude of the secondary flow is a function of the inlet boundary conditions. The secondary flow affects the vortex flow distribution and hence the coefficients. For the SC considered in this study, the most stable WK configurations are located toward the bottom from θ=30deg to 45deg after the curve of the SC begins, and on the top between two stay vanes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".