Cargando…

Data-driven modeling of nonlinear materials in normal-conducting magnets

Accurate numerical modeling of normal-conducting accelerator magnets requires a reliable characterization of the iron saturation and hysteresis as well as a precise knowledge of the magnet geometry as built. Computations of the field quality are not easily achieving the accuracy required by the acce...

Descripción completa

Detalles Bibliográficos
Autores principales: Sorti, Stefano, Petrone, Carlo, Russenschuck, Stephan, Braghin, Francesco
Lenguaje:eng
Publicado: 2022
Materias:
Acceso en línea:https://dx.doi.org/10.1103/PhysRevAccelBeams.25.052401
http://cds.cern.ch/record/2812715
_version_ 1780973357542408192
author Sorti, Stefano
Petrone, Carlo
Russenschuck, Stephan
Braghin, Francesco
author_facet Sorti, Stefano
Petrone, Carlo
Russenschuck, Stephan
Braghin, Francesco
author_sort Sorti, Stefano
collection CERN
description Accurate numerical modeling of normal-conducting accelerator magnets requires a reliable characterization of the iron saturation and hysteresis as well as a precise knowledge of the magnet geometry as built. Computations of the field quality are not easily achieving the accuracy required by the accelerator operation, particularly for eddy-current effects in fast-ramping magnets. This paper proposes a (measurement) data-driven model for the nonlinear magnetization of normal-conducting magnets. The model adopts a volume integral formulation compatible with eddy-current simulations. A two-step updating procedure is applied. The first step is the fitting of material parameters directly in the magnet model. The second step is the updating of the magnetization by measurements of the integral field harmonics. The result is a full-order updated model that can be employed in static or dynamic simulations. Finally, the procedure is validated on an iron-dominated, normal-conducting magnet.
id cern-2812715
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2022
record_format invenio
spelling cern-28127152023-08-09T12:19:42Zdoi:10.1103/PhysRevAccelBeams.25.052401http://cds.cern.ch/record/2812715engSorti, StefanoPetrone, CarloRussenschuck, StephanBraghin, FrancescoData-driven modeling of nonlinear materials in normal-conducting magnetsAccelerators and Storage RingsAccurate numerical modeling of normal-conducting accelerator magnets requires a reliable characterization of the iron saturation and hysteresis as well as a precise knowledge of the magnet geometry as built. Computations of the field quality are not easily achieving the accuracy required by the accelerator operation, particularly for eddy-current effects in fast-ramping magnets. This paper proposes a (measurement) data-driven model for the nonlinear magnetization of normal-conducting magnets. The model adopts a volume integral formulation compatible with eddy-current simulations. A two-step updating procedure is applied. The first step is the fitting of material parameters directly in the magnet model. The second step is the updating of the magnetization by measurements of the integral field harmonics. The result is a full-order updated model that can be employed in static or dynamic simulations. Finally, the procedure is validated on an iron-dominated, normal-conducting magnet.oai:cds.cern.ch:28127152022
spellingShingle Accelerators and Storage Rings
Sorti, Stefano
Petrone, Carlo
Russenschuck, Stephan
Braghin, Francesco
Data-driven modeling of nonlinear materials in normal-conducting magnets
title Data-driven modeling of nonlinear materials in normal-conducting magnets
title_full Data-driven modeling of nonlinear materials in normal-conducting magnets
title_fullStr Data-driven modeling of nonlinear materials in normal-conducting magnets
title_full_unstemmed Data-driven modeling of nonlinear materials in normal-conducting magnets
title_short Data-driven modeling of nonlinear materials in normal-conducting magnets
title_sort data-driven modeling of nonlinear materials in normal-conducting magnets
topic Accelerators and Storage Rings
url https://dx.doi.org/10.1103/PhysRevAccelBeams.25.052401
http://cds.cern.ch/record/2812715
work_keys_str_mv AT sortistefano datadrivenmodelingofnonlinearmaterialsinnormalconductingmagnets
AT petronecarlo datadrivenmodelingofnonlinearmaterialsinnormalconductingmagnets
AT russenschuckstephan datadrivenmodelingofnonlinearmaterialsinnormalconductingmagnets
AT braghinfrancesco datadrivenmodelingofnonlinearmaterialsinnormalconductingmagnets