CFD and LPTN Hybrid Technique to Determine Convection Coefficient in End-winding of TEFC Induction Motor with Copper Rotor
Bibliographic record
Abstract
Convection coefficient in the end-winding is a critical thermal parameter in Lumped Parameter Thermal Network (LPTN) model solution for an accurate motor winding temperature prediction. However, it is a challenging task to determine this convection coefficient due to complex heat and air circulation characteristics in the end-winding region. Until now, all researches focus on Totally Enclosed Fan-cooled (TEFC) Aluminum Rotor Induction Motor (ARIM) with a rotor having fins on its end-rings. But Copper Rotor Induction Motor (CRIM) has a rotor that does not have any fins on its end-rings. Hence, this research will determine convection coefficient in the end-region of Copper Rotor Induction Motor (CRIM) that has smooth rotor end. A Computational Fluid Dynamic (CFD) technique along-with a Lumped Parameter Thermal Network (LPTN) model is proposed to determine this convection coefficient. Thermal experiments on a 20-hp Copper Rotor Induction Motor (CRIM) are conducted to validate this proposed approach.
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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".