Comparative performance analysis of aluminum-rotor and copper-rotor SEIG considering skin effect
Bibliographic record
Abstract
Electricity from wind provides an alternative to conventional generation that could be used to achieve significant reductions in fossil fuel use and consequently industrial emissions. Recent progress in wind power generation has led to the use of grid connected and self excited induction generators (SEIG). Induction machines are commonly used in these applications. Aluminum has been the common conductor material for the squirrel cage of the induction machines for long largely because of lower cost and ease of manufacturing. Recent innovations in material engineering have brought forth copper-rotor induction machines with promising results. Studies on the performance of copper-rotor induction machines working as motors have been reported. However, performance analysis of squirrel-cage copper-rotor SEIGs considering both saturation and skin effect has not yet been carried out. In this paper, a comparative performance analysis of two 7.5 hp aluminum-rotor and copper-rotor SEIG, both theoretically and experimentally, considering saturation as well as skin effect has been presented.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".