Efficiency Improvement of an Electric-Grid Transformer Using the Diamagnetism Characteristics of a Bulk Superconductor
Bibliographic record
Abstract
An innovative method to improve the efficiency of a single-phase electric-grid 125 kVA, 50 Hz shell type and distribution transformer is presented. The diamagnetism characteristic of a bulk high-temperature superconductor (HTS), designed in a specific dimension, is used to construct a magnetic shield around the air gaps that form between the core joints and among the coils of the transformer. Consequently, the shielded flux engages the core area and increases the flux density in the core, resulting in an increase in the output power, and hence an improved transformer efficiency. The transformer was designed and simulated using advanced electromagnetic software. Simulation results indicate that the width and thickness of the HTS material, as its precise location placed on the air gaps around the core and the coils, can be a substantial factor in generating a magnetic shield that results in an efficiency improvement, superior compared to conventional transformers. The most enhanced performance was received for HTS thickness of 2.6 mm, around 2.4% output power improvement compared with a conventional transformer model. In a transformer of this type that efficiency improvement can lead to great energy savings, around 10,000 kWh for half a year of working under load.
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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 | 0.000 |
| 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) | 0.001 | 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".