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    An FMM-FFT Accelerated SIE Simulator for Analyzing EM Wave Propagation in Mine Environments Loaded with Conductors

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    Type
    Article
    Authors
    Yucel, Abdulkadir C. cc
    Sheng, Weitian
    Zhou, Chenming
    Liu, Yang Z.
    Bagci, Hakan cc
    Michielssen, Eric
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2018-02-05
    Online Publication Date
    2018-02-05
    Print Publication Date
    2018
    Permanent link to this record
    http://hdl.handle.net/10754/627220
    
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    Abstract
    A fast and memory efficient 3D full wave simulator for analyzing electromagnetic (EM) wave propagation in electrically large and realistic mine tunnels/galleries loaded with conductors is proposed. The simulator relies on Muller and combined field surface integral equations (SIEs) to account for scattering from mine walls and conductors, respectively. During the iterative solution of the system of SIEs, the simulator uses a fast multipole method - fast Fourier transform (FMM-FFT) scheme to reduce CPU and memory requirements. The memory requirement is further reduced by compressing large data structures via singular value and Tucker decompositions. The efficiency, accuracy, and real-world applicability of the simulator are demonstrated through characterization of EM wave propagation in electrically large mine tunnels/galleries loaded with conducting cables and mine carts.
    Citation
    Yucel AC, Sheng W, Zhou C, Liu YZ, Bagci H, et al. (2018) An FMM-FFT Accelerated SIE Simulator for Analyzing EM Wave Propagation in Mine Environments Loaded with Conductors. IEEE Journal on Multiscale and Multiphysics Computational Techniques: 1–1. Available: http://dx.doi.org/10.1109/jmmct.2018.2802420.
    Sponsors
    This work was supported in part by Alpha Foundation under Grant AFC215-54.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Journal on Multiscale and Multiphysics Computational Techniques
    DOI
    10.1109/jmmct.2018.2802420
    Additional Links
    http://ieeexplore.ieee.org/document/8281076/
    ae974a485f413a2113503eed53cd6c53
    10.1109/jmmct.2018.2802420
    Scopus Count
    Collections
    Articles; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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