Finite-Element Analysis of Unbalanced Magnetic Pull in a Large Hydro-Generator Under Practical Operations
Bibliographic record
Abstract
The rotor eccentricity of a large hydro-generator could cause a huge radial magnetic force, known as an unbalanced magnetic pull (UMP), exerting on the rotor. In this paper, Maxwell stress tensor (MST) method is used to compute the UMP based on the 2-D finite-element (FE) calculation, and the accuracy of UMP FE calculations is investigated. This paper presents a new method for the FE calculation of UMP due to rotor eccentricity in large hydro-generators. This method significantly overcomes difficulties of loading over thousand current sources for the UMP FE calculation of large hydro-generators with hundred stator slots operating under loads. In this paper, the UMP on a 240 MW, 88 poles, 720-slot hydro-generator, for various degrees of rotor eccentricity, are calculated and compared for operations with no load, half rated, and rated load. Also, the UMP on this hydro-generator is calculated when the rotor windings are subjected to a short-circuited fault condition. The method proposed in this paper was successfully used to study the vibration of Three-Gorge generation units in China.
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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) | 0.000 | 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 | 0.001 | 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 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".