Data-Driven Modeling of Accelerator Magnets
Abstract
We present a methodology that enables data-driven modeling and traceable design workflows of accelerator magnets by combining numerical field simulations with tests and magnetic measurements. The aim is to create models updated by magnetic measurements that allow for the extrapolation of performance parameters regarding different magnet powering cycles, manufacturing defects, and material parameters while mitigating the uncertainties in both the simulations and measurements.
Fields of Study & Subjects
Particle accelerators and beam dynamics
Superconducting Materials and Applications
Control Systems and Identification
Publication details
- Journal / source
- IEEE Transactions on Magnetics
- Volume
- 62
- Issue
- 7
- Pages
- 7503306–7503306
- Publication date
- 27 January 2026
- Language
- EN