A combined reduced order‐full order methodology for the solution of 3D magneto‐mechanical problems with application to magnetic resonance imaging scanners
| Autor: | Antonio J. Gil, Sergio Zlotnik, M. Mallett, M. Seoane, Paul D. Ledger |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Doctorat Erasmus Mundus en Simulació en Enginyeria i Desenvolupament de l'Emprenedoria, Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental, Universitat Politècnica de Catalunya. LACÀN - Mètodes Numèrics en Ciències Aplicades i Enginyeria |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Proper Orthogonal Decomposition
Multifield systems Full order 02 engineering and technology Newton methods 01 natural sciences Reduced order Matemàtiques i estadística::Anàlisi numèrica [Àrees temàtiques de la UPC] symbols.namesake Magneto-mechanical coupling 0203 mechanical engineering medicine 70 Mechanics of particles and systems::70H Hamiltonian and Lagrangian mechanics [Classificació AMS] Applied mathematics Order (group theory) 0101 mathematics Hamiltonian systems Magneto Lagrangian Physics Numerical Analysis medicine.diagnostic_test ROM Applied Mathematics Numerical analysis General Engineering Magnetic resonance imaging MRI scanner 010101 applied mathematics 020303 mechanical engineering & transports Hamilton Sistemes de symbols Proper orthogonal decomposition |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | This is the peer reviewed version of the following article: Seoane, M. [et al.]. 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", 1 Gener 2020, vol. 121, núm. 16, p. 3529-3559. , which has been published in final form athttps://onlinelibrary.wiley.com/doi/abs/10.1002/nme.6369. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. 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. Generalitat de Catalunya, 2017‐SGR‐1278; Marie Sklodowska‐Curie Innovative Training Network AdMoRe, 675919; Spanish Ministry of Economy and Competitiveness, DPI2017‐85139‐C2‐2‐R |
| Databáze: | OpenAIRE |
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