BEM-Based Magnetic Field Reconstruction by Ensemble Kálmán Filtering
Liebsch, M., Russenschuck, S., & Kurz, S. (2022). BEM-Based Magnetic Field Reconstruction by Ensemble Kálmán Filtering. Computational methods in applied mathematics, Early online. https://doi.org/10.1515/cmam-2022-0121
Published inComputational methods in applied mathematics
© 2022 the author(s)
Magnetic fields generated by normal or superconducting electromagnets are used to guide and focus particle beams in storage rings, synchrotron light sources, mass spectrometers, and beamlines for radiotherapy. The accurate determination of the magnetic field by measurement is critical for the prediction of the particle beam trajectory and hence the design of the accelerator complex. In this context, state-of-the-art numerical field computation makes use of boundary-element methods (BEM) to express the magnetic field. This enables the accurate computation of higher-order partial derivatives and local expansions of magnetic potentials used in efficient numerical codes for particle tracking. In this paper, we present an approach to infer the boundary data of an indirect BEM formulation from magnetic field measurements by ensemble Kálmán filtering. In this way, measurement uncertainties can be propagated to the boundary data, magnetic field and potentials, and to the beam related quantities derived from particle tracking. We provide results obtained from real measurement data of a curved dipole magnet using a Hall probe mapper system. ...
PublisherWalter de Gruyter GmbH
ISSN Search the Publication Forum1609-4840
Publication in research information system
MetadataShow full item record
Additional information about fundingThe work of Melvin Liebsch is supported by the Graduate School CE within the Centre for Computational Engineering at Technische Universität Darmstadt.
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