A combined reduced order‐full order methodology for the solution of 3D magneto‐mechanical problems with application to magnetic resonance imaging scanners

Seoane, M.; Ledger, P. D.; Gil, A. J.; Zlotnik, S.; Mallett, M.

Abstract

The design of a new magnetic resonance imaging (MRI) scanner requires multiple numerical simulations of the same magneto-mechanical problem for varying model parameters, such as frequency and electric conductivity, in order to ensure that the vibrations, noise, and heat dissipation are minimized. The high computational cost required for these repeated simulations leads to a bottleneck in the design process due to an increased design time and, thus, a higher cost. To alleviate these issues, the application of reduced order modeling techniques, which are able to find a general solution to high-dimensional parametric problems in a very efficient manner, is considered. Building on the established proper orthogonal decomposition technique available in the literature, the main novelty of this work is an efficient implementation for the solution of 3D magneto-mechanical problems in the context of challenging MRI configurations. This methodology provides a general solution for varying parameters of interest. The accuracy and efficiency of the method are proven by applying it to challenging MRI configurations and comparing with the full-order solution.

Citation

Seoane, M., Ledger, P. D., Gil, A. J., Zlotnik, S., & Mallett, M. (2020). A combined reduced order‐full order methodology for the solution of 3D magneto‐mechanical problems with application to magnetic resonance imaging scanners. International Journal for Numerical Methods in Engineering, 121(16), 3529-3559. https://doi.org/10.1002/nme.6369

• Journal Article Type: Article
• Acceptance Date: Mar 17, 2020
• Online Publication Date: May 15, 2020
• Publication Date: Aug 30, 2020
• Deposit Date: Jun 12, 2023
• Journal: International Journal for Numerical Methods in Engineering
• Print ISSN: 0029-5981
• Electronic ISSN: 1097-0207
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 121
• Issue: 16
• Pages: 3529-3559
• DOI: https://doi.org/10.1002/nme.6369
• Keywords: Applied Mathematics; General Engineering; Numerical Analysis
• Additional Information: Received: 2019-09-13; Accepted: 2020-03-17; Published: 2020-05-15