2958887 SzGeCERN 20260417152515.0 DOI IEEE 10.1109/ECCE-Asia49820.2021.9478990 oai:cds.cern.ch:2958887 cerncds:CERN https://inspirehep.net/api/oai2d oai:inspirehep.net:3143695 2026-04-14T13:37:27Z 2026-04-15T04:20:38Z marcxml Inspire 3143695 eng Wolstrup, Anders Frem Denmark, Tech. U. IEEE Automatic Frequency-Domain Modelling of Superconducting Magnets and its Usability to Model General Inductors 2021 7 p IEEE This paper focuses on the development of a Python dataclass and SWAN notebooks allowing for automatic generation of PSPICE© of the Large Hydron Collider (LHC) superconducting electromagnets and circuits installed at CERN. The models consist of inductors, resistors and capacitors, as well as RL-loops, modelling the behaviour of the magnets and circuits, including eddy-current effects. The dataclass can accommodate several types of magnets, and allows for custom fitting to measurements. Furthermore, the dataclass produces three different models for each magnet or circuit. The models differ in complexity trading computation time for accuracy. One of the circuit models was validated by experimental data. The dataclass was used to generate models of 37 LHC magnets and 63 circuits, as a part of the STEAM LHC circuit model library. The automatic functionality of the library provides an easy and quick way to both add and maintain the models in the library. Finally, the dataclass’ usability in regards to general inductors is assessed. publication IEEE 2021 For annual report SzGeCERN Accelerators and Storage Rings author Computational modeling author Large Hadron Collider author Magnetic cores author Superconducting magnets author Libraries author Integrated circuit modeling author Inductors ARTICLE CERN Ravaioli, Emmanuele CERN Zsurzsan, Tiberiu Gabriel Denmark, Tech. U. Zhang, Zhe Denmark, Tech. U. 1312-1318 IEEE Conf. ECCEAsia 2021 C21-05-24.5 2021 h 202616 13 2959026 1312-1318 online20210524 ARTICLE ConferencePaper