基于离散经验插值法的磁共振成像加速域分解FEM-BEM求解器

N. Farnoosh, A. Polimeridis, T. Klemas, L. Daniel
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引用次数: 1

摘要

提出了一种多域电磁散射的有限元和场积分方程联合区域分解方法。主要的计算瓶颈是构建捕获不同域之间相互作用的密集耦合阻抗矩阵块。为了加速这种耦合计算,A. Hochman等[1]提出了随机奇异值分解(rSVD)和离散经验插值(DEIM)相结合的方法。该算法将每个域上等效电流的入射场的计算简化为几个观测点,这些观测点可以通过DEIM算法进行最佳和自动定位。此外,该方法生成的耦合块的压缩形式显著降低了与全局系统矩阵迭代解相关的内存需求和计算成本。在本文中,我们重点开发了一种结合有限元法(FEM)和边界元法(BEM)的区域分解求解器的实现方法。最后给出了一个简化的磁共振成像(MRI)在人体上的散射结果,以验证我们的代码实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accelerated domain decomposition FEM-BEM solver for magnetic resonance imaging (MRI) via discrete empirical interpolation method
A finite element and combined field integral equation domain decomposition approach is presented for electromagnetic scattering from multiple domains. The main computational bottleneck is the construction of the dense coupling impedance matrix blocks capturing the interactions between different domains. In order to accelerate such coupling computation, A. Hochman et al. in [1] proposed the combination of the randomized singular value decomposition (rSVD) and of the discrete empirical interpolation method (DEIM). The computation of the incident fields due to equivalent currents on each domain is reduced to just a few observation points that can be located optimally and automatically by the DEIM algorithm. Furthermore, the compressed form of the coupling blocks generated by that approach significantly reduces the memory requirement and computational cost associated with the iterative solution of the global system matrix. In this paper, we focus on developing an implementation of such approach for a domain decomposition solver that combines finite element method (FEM) with boundary element method (BEM). Results on a simplified magnetic resonance imaging (MRI) scattering on human body are finally presented to validate our code implementation.
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