A regularised-adaptive Proper Generalised Decomposition implementation for coupled magneto-mechanical problems with application to MRI scanners

Author (s): Barroso, G., Gil, A.J., Ledger, P.D., Mallett, M. and Huerta, A.
Journal: Computer Methods in Applied Mechanics and Engineering

Volume: 358
Date: 2020

Abstract:
Latest developments in high-strength Magnetic Resonance Imaging (MRI) scanners with in-built high resolution, have dramatically enhanced the ability of clinicians to diagnose tumours and rare illnesses. However, their high-strength transient magnetic fields induce unwanted eddy currents in shielding components, which result in fast vibrations, noise, imaging artefacts and, ultimately, heat dissipation, boiling off the helium used to super-cool the magnets. Optimum MRI scanner design requires the capturing of complex electro-magneto-mechanical interactions with high fidelity computational tools. During production cycles, this is known to be extremely expensive due to the large number of configurations that need to be tested. There is an urgent need for the development of new cost-effective methods whereby previously performed computations can be assimilated as training solutions of a surrogate digital twin model to allow for real-time simulations. In this paper, a Reduced Order Modelling technique based on the Proper Generalised Decomposition method is presented for the first time in the context of MRI scanning design, with two distinct novelties. First, the paper derives from scratch the offline higher dimensional parametrised solution process of the coupled electro-magneto-mechanical problem at hand and, second, a regularised adaptive methodology is proposed for the circumvention of numerical singularities associated with the ill-conditioning of the discrete system in the vicinity of resonant modes. A series of numerical examples are presented in order to illustrate, motivate and demonstrate the validity and flexibility of the considered approach.

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Bibtex:

@article{GB-BGLMH:20}
        Author = {Guillem Barroso and Antonio J. Gil$ and Paul D. Ledger 
                  and Mike Mallett and Antonio Huerta},
        Title = {A regularised-adaptive {P}roper {G}eneralised {D}ecomposition 
                 implementation for coupled magneto-mechanical problems with 
                 application to {MRI} scanners},
        Fjournal = {Computer Methods in Applied Mechanics and Engineering},
        Journal = {Comput. Methods Appl. Mech. Eng.},
        Volume = {358},
        Pages = {112640},
        Year = {2020},
        Doi = {10.1016/j.cma.2019.112640},
        }