Prediction and investigation between impeller blade shape parameters and performance parameters in CFD and ANN
Bibliographic record
Abstract
The blade shape parameters have a remarkable effect on the centrifugal pump performance. In order to reveal the relationship between these parameters and pump performance, a single channel was regarded as the research object to calculate its performance by numerical simulation, and the performance was measured on an experimental rig. The optimized ANN is proposed, and it is proved to be highly accurate. The ANN correlation coefficient of the total response could be above 0.997 after thousands of retaining. The sorts and degrees affecting performance parameters were found out by gray relation analysis. It was found that the blade angles at the leading edge were more influential for reaction force, head and minimum pressure, while the wrap angles had greater impact for efficiency. Furthermore, a multiple linear regression model was established to quantify the weight and trend of the influence of blade shape parameters on performance. The results provide a reference guide for the optimized design of centrifugal impeller to improve pump performance.
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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".