Artificial neural network interpolation for magnetic field mapping in an air-core HTS quadruple magnet

Geonwoo Baek, Junseong Kim, Tae Kuk Ko, Sangjin Lee

Research output: Contribution to journalArticlepeer-review

Abstract

An air-core high-temperature superconducting (HTS) quadruple magnet is currently being designed and fabricated at the Applied Superconductivity Laboratory, Yonsei University, in collaboration with Uiduk University. It is composed of eight double-pancake racetrack coils, each wound with 4-mm REBCO tapes manufactured by SuNAM Co., Inc. The Metal-as-Insulation technique will be used to reduce no-insulation charging delays. The gradient, uniformity and effective length of the initially-designed air-core quadruple magnet are 3.1 Tm−1, below 0.5%, and 209.0 mm, respectively. However, the magnet to be fabricated will be different from the designed magnet owing to manufacturing uncertainties. Therefore, magnetic field measurements must be performed in the volume of interest of the magnet. As it is impossible to measure the magnetic field at all points, it is crucial to obtain a mapping algorithm that can calculate the magnetic field in the volume of interest based on the measured field at several points. Herein, a mapping method using the discrete Fourier transform and artificial neural network interpolation was presented. To verify the mapping method, a mapping simulation of the designed magnet was performed and analyzed.

Original languageEnglish
Article number103043
JournalCryogenics
Volume107
DOIs
Publication statusPublished - 2020 Apr

Bibliographical note

Funding Information:
This work was supported by “Human Resources Program in Energy Technology” of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea, and by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (Nos. 20184030202270 and 2017R1A2B3012208 ).

Publisher Copyright:
© 2020

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Physics and Astronomy(all)

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