Parallel preconditioners and high order elements for microwave imaging

Bonazzoli, M. and Dolean, V. and Rapetti, F. and Tournier, P. -H. (2017) Parallel preconditioners and high order elements for microwave imaging. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields. (https://doi.org/10.1002/jnm.2229)

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Abstract

This paper combines the use of high order finite element methods with parallel preconditioners of domain decomposition type for solving electromagnetic problems arising from brain microwave imaging. The numerical algorithms involved in such complex imaging systems are computationally expensive since they require solving the direct problem of Maxwell's equations several times. Moreover, wave propagation problems in the high frequency regime are challenging because a sufficiently high number of unknowns is required to accurately represent the solution. In order to use these algorithms in practice for brain stroke diagnosis, running time should be reasonable. The method presented in this paper, coupling high order finite elements and parallel preconditioners, makes it possible to reduce the overall computational cost and simulation time while maintaining accuracy.

  • Item type:Article
    ID code:59510
    Dates:
    Date
    Event
    15 February 2017
    Published
    15 February 2017
    Published Online
    1 September 2016
    Accepted
    Notes:This is the peer reviewed version of the following article: Bonazzoli, M., Dolean, V., Rapetti, F., & Tournier, P. -H. (2016). Parallel preconditioners and high order elements for microwave imaging. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields., which will be published in final form at https://doi.org/10.1002/jnm.2229 . This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
    Subjects:Science > Mathematics
    Department:Faculty of Science > Mathematics and Statistics
    Depositing user: Pure Administrator
    Date deposited:20 Jan 2017 11:45
    Last modified:08 Apr 2024 23:02
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/59510
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