Optimally Segmented Permanent Magnet Structures
Title | Optimally Segmented Permanent Magnet Structures |
Publication Type | Journal Article |
Year of Publication | 2016 |
Authors | Insinga, A. R., Bjørk, R., Smith, A., Bahl, C. R. H. |
Journal | IEEE Transactions on Magnetics |
Volume | 52 |
Pagination | 1–6 |
ISSN | 0018-9464 |
Keywords | 2D magnetic system, composability, compositionality, cyber physical systems, finite element analysis, linear objective functional, magnetic devices, Magnetic domains, Magnetic noise, Magnetic Remanence, Magnetic separation, Magnetic shielding, optimal segmentation, optimisation, Optimization, Optimization methods, permanent magnet machines, permanent magnet structures, Permanent magnets, Permeability, pubcrawl, remanence, remanent flux density vector, Resiliency, Soft magnetic materials |
Abstract | We present an optimization approach that can be employed to calculate the globally optimal segmentation of a 2-D magnetic system into uniformly magnetized pieces. For each segment, the algorithm calculates the optimal shape and the optimal direction of the remanent flux density vector, with respect to a linear objective functional. We illustrate the approach with results for magnet design problems from different areas, such as a permanent magnet electric motor, a beam-focusing quadrupole magnet for particle accelerators, and a rotary device for magnetic refrigeration. |
URL | https://ieeexplore.ieee.org/document/7518613/ |
DOI | 10.1109/TMAG.2016.2593685 |
Citation Key | insinga_optimally_2016 |
- optimal segmentation
- Soft magnetic materials
- Resiliency
- remanent flux density vector
- remanence
- pubcrawl
- Permeability
- Permanent magnets
- permanent magnet structures
- permanent magnet machines
- Optimization methods
- optimization
- optimisation
- 2D magnetic system
- Magnetic shielding
- Magnetic separation
- Magnetic Remanence
- Magnetic noise
- Magnetic domains
- magnetic devices
- linear objective functional
- finite element analysis
- cyber physical systems
- Compositionality
- composability