Predicting Turbine Performance of High Specific Speed Pumps Using CFD
Bibliographic record
Abstract
A pump with a specific speed of 12000 was chosen to operate as a turbine (PAT) for a micro-hydro site having 5 m of head. Turbine performance of the pump was unavailable so it was simulated using CFD. The CFD model was first verified by comparison of simulated pump performance and manufacturer data. Simulated PAT performance covered a range of flow rates, from one to three times that of pump best efficiency point (BEP), for blade angles of 0 and ± 4°. The PAT BEP was located at a flow rate of 1.4 times that of pump BEP and a head of 1.6 times. For the specific site this corresponded to a shaft power of 32 k W and a flow rate of 770 1/s. The PAT was found to have an extended range of good efficiency, > 60%, for up to 3 times the pump BEP flow rate.
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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) | 0.001 | 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 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".