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A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners

Guillem Barroso, M. Seoane, Antonio Gil Orcid Logo, Paul Ledger, M. Mallett, A. Huerta

Computer Methods in Applied Mechanics and Engineering, Volume: 370, Start page: 113271

Swansea University Authors: Guillem Barroso, Antonio Gil Orcid Logo, Paul Ledger

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Abstract

Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to industry, due to the large variability in material parameters and geometrical configurations that need to be tested during the early design phase. This process can be highly optimised through the empl...

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Published in: Computer Methods in Applied Mechanics and Engineering
ISSN: 0045-7825
Published: Elsevier BV 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa54652
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This process can be highly optimised through the employment of user-friendly computational metamodels constructed on the basis of Reduced Order Modelling (ROM) techniques, where high-dimensional parametric offline solutions are obtained, stored and assimilated in order to be efficiently queried in real time. This paper presents a novel Proper Generalised Decomposition (PGD) based metamodel for the analysis of electro-magneto-mechanical interactions in the context of MRI scanner design, with three distinct novelties. First, the paper derives, from scratch, a five-dimensional parametrised offline solution process, expressed in terms of (axisymmetric) cylindrical coordinates, external excitation frequency, electrical conductivity of the embedded shields and strength of the static magnetic field. Second, by exploiting the staggered nature of the coupled problem at hand, an efficient sequential PGD algorithm is derived and compared against a previously published monolithic PGD algorithm. As a third novelty, the paper draws some interesting comparisons against an alternative tailor-made ROM technique, where the electromagnetic equations are solved using a Proper Orthogonal Decomposition model. 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spelling v2 54652 2020-07-06 A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners 416f4b069a03346279718e1d78fb55ec Guillem Barroso Guillem Barroso true false 1f5666865d1c6de9469f8b7d0d6d30e2 0000-0001-7753-1414 Antonio Gil Antonio Gil true false 068dd31af167bcda33878951b2a01e97 Paul Ledger Paul Ledger true false 2020-07-06 EEN Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to industry, due to the large variability in material parameters and geometrical configurations that need to be tested during the early design phase. This process can be highly optimised through the employment of user-friendly computational metamodels constructed on the basis of Reduced Order Modelling (ROM) techniques, where high-dimensional parametric offline solutions are obtained, stored and assimilated in order to be efficiently queried in real time. This paper presents a novel Proper Generalised Decomposition (PGD) based metamodel for the analysis of electro-magneto-mechanical interactions in the context of MRI scanner design, with three distinct novelties. First, the paper derives, from scratch, a five-dimensional parametrised offline solution process, expressed in terms of (axisymmetric) cylindrical coordinates, external excitation frequency, electrical conductivity of the embedded shields and strength of the static magnetic field. Second, by exploiting the staggered nature of the coupled problem at hand, an efficient sequential PGD algorithm is derived and compared against a previously published monolithic PGD algorithm. As a third novelty, the paper draws some interesting comparisons against an alternative tailor-made ROM technique, where the electromagnetic equations are solved using a Proper Orthogonal Decomposition model. A series of numerical examples are presented in order to illustrate, motivate and demonstrate the validity and potential of the considered approach, especially in terms of cost reduction. Journal Article Computer Methods in Applied Mechanics and Engineering 370 113271 Elsevier BV 0045-7825 Coupled magneto-mechanical problems, MRI scanners, Design optimisation, Reduced order modelling, Proper Generalised Decomposition, Real time simulation 1 10 2020 2020-10-01 10.1016/j.cma.2020.113271 COLLEGE NANME Engineering COLLEGE CODE EEN Swansea University 2022-12-05T11:35:39.9394517 2020-07-06T12:35:22.3440466 College of Engineering Engineering Guillem Barroso 1 M. Seoane 2 Antonio Gil 0000-0001-7753-1414 3 Paul Ledger 4 M. Mallett 5 A. Huerta 6 54652__17648__c162a3e408d3413eb91ab3ade96aa1e7.pdf 54652.pdf 2020-07-06T12:38:01.3785460 Output 2928017 application/pdf Accepted Manuscript true 2021-07-24T00:00:00.0000000 Released under the terms of a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND). true English
title A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners
spellingShingle A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners
Guillem Barroso
Antonio Gil
Paul Ledger
title_short A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners
title_full A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners
title_fullStr A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners
title_full_unstemmed A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners
title_sort A staggered high-dimensional Proper Generalised Decomposition for coupled magneto-mechanical problems with application to MRI scanners
author_id_str_mv 416f4b069a03346279718e1d78fb55ec
1f5666865d1c6de9469f8b7d0d6d30e2
068dd31af167bcda33878951b2a01e97
author_id_fullname_str_mv 416f4b069a03346279718e1d78fb55ec_***_Guillem Barroso
1f5666865d1c6de9469f8b7d0d6d30e2_***_Antonio Gil
068dd31af167bcda33878951b2a01e97_***_Paul Ledger
author Guillem Barroso
Antonio Gil
Paul Ledger
author2 Guillem Barroso
M. Seoane
Antonio Gil
Paul Ledger
M. Mallett
A. Huerta
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container_start_page 113271
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description Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to industry, due to the large variability in material parameters and geometrical configurations that need to be tested during the early design phase. This process can be highly optimised through the employment of user-friendly computational metamodels constructed on the basis of Reduced Order Modelling (ROM) techniques, where high-dimensional parametric offline solutions are obtained, stored and assimilated in order to be efficiently queried in real time. This paper presents a novel Proper Generalised Decomposition (PGD) based metamodel for the analysis of electro-magneto-mechanical interactions in the context of MRI scanner design, with three distinct novelties. First, the paper derives, from scratch, a five-dimensional parametrised offline solution process, expressed in terms of (axisymmetric) cylindrical coordinates, external excitation frequency, electrical conductivity of the embedded shields and strength of the static magnetic field. Second, by exploiting the staggered nature of the coupled problem at hand, an efficient sequential PGD algorithm is derived and compared against a previously published monolithic PGD algorithm. As a third novelty, the paper draws some interesting comparisons against an alternative tailor-made ROM technique, where the electromagnetic equations are solved using a Proper Orthogonal Decomposition model. A series of numerical examples are presented in order to illustrate, motivate and demonstrate the validity and potential of the considered approach, especially in terms of cost reduction.
published_date 2020-10-01T11:35:39Z
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