Numerical simulation for influence of rear wear ring and balance hole on performance of the canned motor pump
Bibliographic record
Abstract
Abstract Canned motor pumps are widely used in chemical and nuclear industries for transporting hazardous fluids. There are few studies on the effects of structural changes to the rear wear ring and balance hole on leakage and axial force in canned motor pumps, and the mechanisms for improving rear pump chamber flow have not been revealed. This paper modifies the rear wear ring and balance hole to reveal mechanisms of their impact on rear pump chamber flow and demonstrates that the improved designs reduce axial force, minimize leakage, and enhance operational stability. The results show that increasing the rear wear ring clearance width stabilizes the axial force, reaching equilibrium when the clearance is 0.4 mm ( = 0.4 mm). The inverted trapezoid rear wear ring exhibits the lowest leakage, averaging a 15.97% reduction across flow rates. Changes to the rear wear ring clearance structure are found to reduce leakage and rear pump chamber pressure while slightly improving efficiency. Adjusting the balance hole diameter reduces the leakage backflow interference on the impeller internal flow and promotes the vortex structure development within the balance hole. Changes to radial position of the balance hole effectively reduce leakage. When balance holes radial position is 59 mm ( = 59 mm), the vortex structure can be utilized to control impact of leakage flow on the mainstream within impeller. This paper provides certain theoretical reference for the design, optimization, and application of canned motor pumps.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".