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Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems / GUILLEM GASSIOT

Swansea University Author: GUILLEM GASSIOT

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DOI (Published version): 10.23889/SUthesis.58977

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...

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Published: Swansea 2021
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
Supervisor: Gil, Antonio J. ; Ledger, Paul D.
URI: https://cronfa.swan.ac.uk/Record/cronfa58977
first_indexed 2021-12-08T15:58:48Z
last_indexed 2021-12-09T04:17:29Z
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recordtype RisThesis
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However, their high-strength transient magnetic &#xFB01;elds induce unwanted eddy currents in shielding components, which result in high-frequency vibrations, noise, imaging artefacts and, ultimately, heat dissipation and boiling o&#xFB00; of the helium used to super-cool the magnets. Optimum MRI scanner design requires the capturing of complex electro-magneto-mechanical interactions with high &#xFB01;delity computational tools. Moreover, manufacturing new MRI scanners still represents a computational challenge to industry due to the large variability in material parameters and geometrical con&#xFB01;gurations 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 o&#xFB04;ine solutions are obtained, stored and assimilated in order to be e&#xFB03;ciently queried in real time.This thesis presents a novel a priori Proper Generalised Decomposition (PGD) computational framework for the analysis of the electro-magneto-mechanical inter-actions in the context of MRI scanner design to address the urgent need for the development of new cost-e&#xFB00;ective methods, whereby previously performed compu-tations can be assimilated as training solutions of a surrogate digital twin model to allow for real-time simulations. The PGD methodology is derived for coupled electro-magneto-mechanical problems in an axisymmetric Lagrangian setting, in-cluding the possibility to vary several material and geometrical parameters (as part of the high-dimensional o&#xFB04;ine solution), that are relevant for the industrial part-ner of the project, Siemens Healthineers. A regularised-adaptive strategy and a staggered PGD approach are proposed in order to enhance the accuracy and robust-ness of the PGD algorithm while preserving its a priori nature. The Lagrangian adaptation of the governing equations will allow for a comparison between staggered and monolithic solvers, where the staggered approach will be shown to enhance the robustness and accuracy of the PGD technique. 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spelling 2021-12-08T17:25:23.2971255 v2 58977 2021-12-08 Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems 75d5ddc7a394e677ddac9c617ade7b8d GUILLEM GASSIOT GUILLEM GASSIOT true false 2021-12-08 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 high-frequency vibrations, noise, imaging artefacts and, ultimately, heat dissipation and boiling off of 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. Moreover, manufacturing new MRI scanners still 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 thesis presents a novel a priori Proper Generalised Decomposition (PGD) computational framework for the analysis of the electro-magneto-mechanical inter-actions in the context of MRI scanner design to address the urgent need for the development of new cost-effective methods, whereby previously performed compu-tations can be assimilated as training solutions of a surrogate digital twin model to allow for real-time simulations. The PGD methodology is derived for coupled electro-magneto-mechanical problems in an axisymmetric Lagrangian setting, in-cluding the possibility to vary several material and geometrical parameters (as part of the high-dimensional offline solution), that are relevant for the industrial part-ner of the project, Siemens Healthineers. A regularised-adaptive strategy and a staggered PGD approach are proposed in order to enhance the accuracy and robust-ness of the PGD algorithm while preserving its a priori nature. The Lagrangian adaptation of the governing equations will allow for a comparison between staggered and monolithic solvers, where the staggered approach will be shown to enhance the robustness and accuracy of the PGD technique. Moreover, geometric changes in the computational domain will be accounted for in the PGD solution by using a PGD-projection technique that will enable the computation of a separable expression even for geometrical variations, preserving thus the efficiency of the online PGD stage. A set of numerical problems will be presented in order to validate the PGD formula-tion, which will be benchmarked against the full order (reference) model. Moreover, a comparison between two families of ROM methods, the a priori PGD and the a posteriori Proper Orthogonal Decomposition (POD), will also be performed in order to assess and compare different ROM strategies. E-Thesis Swansea 8 12 2021 2021-12-08 10.23889/SUthesis.58977 COLLEGE NANME COLLEGE CODE Swansea University Gil, Antonio J. ; Ledger, Paul D. Doctoral Ph.D 2021-12-08T17:25:23.2971255 2021-12-08T15:20:34.9095749 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised GUILLEM GASSIOT 1 58977__21850__ef0c09e3cb53428c9b561aec09a4d0c7.pdf Barroso_Guillem_PhD_Thesis_Final_Redacted_Signature.pdf 2021-12-08T17:15:52.3141242 Output 29130578 application/pdf E-Thesis – open access true Copyright: The author, Guillem Barroso Gassiot, 2020. true eng
title Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems
spellingShingle Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems
GUILLEM GASSIOT
title_short Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems
title_full Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems
title_fullStr Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems
title_full_unstemmed Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems
title_sort Towards MRI scanner design: the Proper Generalised Decomposition in the context of coupled magneto-mechanical problems
author_id_str_mv 75d5ddc7a394e677ddac9c617ade7b8d
author_id_fullname_str_mv 75d5ddc7a394e677ddac9c617ade7b8d_***_GUILLEM GASSIOT
author GUILLEM GASSIOT
author2 GUILLEM GASSIOT
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publishDate 2021
institution Swansea University
doi_str_mv 10.23889/SUthesis.58977
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
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description 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 high-frequency vibrations, noise, imaging artefacts and, ultimately, heat dissipation and boiling off of 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. Moreover, manufacturing new MRI scanners still 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 thesis presents a novel a priori Proper Generalised Decomposition (PGD) computational framework for the analysis of the electro-magneto-mechanical inter-actions in the context of MRI scanner design to address the urgent need for the development of new cost-effective methods, whereby previously performed compu-tations can be assimilated as training solutions of a surrogate digital twin model to allow for real-time simulations. The PGD methodology is derived for coupled electro-magneto-mechanical problems in an axisymmetric Lagrangian setting, in-cluding the possibility to vary several material and geometrical parameters (as part of the high-dimensional offline solution), that are relevant for the industrial part-ner of the project, Siemens Healthineers. A regularised-adaptive strategy and a staggered PGD approach are proposed in order to enhance the accuracy and robust-ness of the PGD algorithm while preserving its a priori nature. The Lagrangian adaptation of the governing equations will allow for a comparison between staggered and monolithic solvers, where the staggered approach will be shown to enhance the robustness and accuracy of the PGD technique. Moreover, geometric changes in the computational domain will be accounted for in the PGD solution by using a PGD-projection technique that will enable the computation of a separable expression even for geometrical variations, preserving thus the efficiency of the online PGD stage. A set of numerical problems will be presented in order to validate the PGD formula-tion, which will be benchmarked against the full order (reference) model. Moreover, a comparison between two families of ROM methods, the a priori PGD and the a posteriori Proper Orthogonal Decomposition (POD), will also be performed in order to assess and compare different ROM strategies.
published_date 2021-12-08T05:12:11Z
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score 11.3749895

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