Comparison of Measured and Predicted Inductance per Cell for a Travelling Wave Kicker Magnet
Bibliographic record
Abstract
Many present day kicker magnets must have a relatively short field rise time, and low flat-top and postpulse ripple. In order to design the electrical circuit for a kicker magnet with the required specifications for field quality, it is necessary to quantify the effect of end-fields on the inductance distribution throughout the travelling wave kicker magnet. This paper presents the results of an electromagnetic analysis of a relatively short, 10 cell, prototype travelling wave kicker magnet using a three dimensional code capable of modelling eddy-currents: in order to verify the predictions, inductance measurements are also presented. 1 INTRODUCTION As part of the Canadian contribution to CERN LHC, TRIUMF is assisting with the design of the injection system[1, 2]. 3D simulations of the LHC kicker magnets will be carried out: these simulations will permit inductance per cell to be calculated, and will include end effects. In order to prove the integrity of the 3D software, for simulat...
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".