What does it take to design a low inrush large induction motor?
Bibliographic record
Abstract
The need for a low inrush A. C. motor is usually based on a weak power system where conventional starters are not desirable. Low inrush motors are often used in marine services like Floating Production, Storage & Offloading (FPSO) and Liquefied Natural Gas (LNG) plants where weight and space is at a premium. They are also needed for pulpwood refiners in paper industry or at remote sites like mining operation where the electrical power system is weak, and there is a concern that a normal inrush motor could create a significant voltage drop causing a negative impact to other equipment in the electrical system. In such cases, a low inrush motor is preferred even though there may be some operating performance drawbacks. Customized low inrush motors are challenging to a machine designer when one is trying to meet application as well as performance requirements. This paper covers all those areas of concern and addresses them in order to design low inrush induction motors.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".