Traditional approaches to engineering design employ low order finite element discretisations and traditional approaches to finite element analysis. However, such methodologies require dense discretisations and lead to expensive computations in order to ensure sufficient accuracy for today’s modern designs. The latest developments in finite element analysis offer the possibilities for high levels of accuracy within a computational competitive time scale, but, to date, have not been applied in an industrial context.

In this PhD project the chosen application of interest is a clinical MRI system. Siemens Magnet Technology are interested in understanding the coupled electro-magneto- mechanical response of its conducting components making up an MRI scanner and the effects that changes in its design have on its performance and vibrations. The magnetic coupling between the various components produces secondary magnetic fields which are also coupled back. An accurate prediction of these secondary magnetic fields is essential to predict the impact on imaging performance, especially in three dimensions. To do this, the coupled set of elasticity equations, for describing the mechanical response, and Maxwell equations, for electromagnetic response, must be solved.

This PhD will first develop a computational framework based on advanced hp-finite element technology and efficient algorithms for the solution of resulting non-linear equation system in a transient context. This will help Siemens Magnet Technology to improve its MRI coil designs and comparisons against industrial designs will be undertaken to ensure that the high-fidelity model of a realistic three-dimensional configuration is fully benchmarked. The PhD will become a member of an active research group working on the development and application of computational techniques in coupled problems.

PhD candidate: Marcos Seoane (Siemens, Swansea University, Universitat Politècnica de Catalunya)

Academic supervisors: Prof. A.J. Gil, Dr. P. Ledger (SU), Prof. A. Huerta, Dr. S. Zlotnik (UPC)

Industrial supervisor: Dr. M. Mallet (Siemens)