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Efficient Multilevel Compressed Block Decomposition for Large-Scale Electromagnetic Problems using Asymptotic Phasefront Extraction

机译:渐近相前提取用于大规模电磁问题的高效多级压缩块分解

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摘要

A large dense complex linear system can be obtained when solving an electromagnetic scattering problem with the surface integral equation approach. To analyze the large dense complex linear system efficiently, the multilevel compressed block decomposition (MLCBD) is used to accelerate the matrix-vector multiplication operations. Although the MLCBD is efficient compared with the direct method of moments, it is still less efficient for the large-scale electromagnetic problems. Therefore, an efficient version of MLCBD is proposed in this paper. It utilizes the asymptotic phasefront extraction (APE) to reduce the exorbitant dependence on computer storage and solution time in the MLCBD for analyzing the large-scale electromagnetic problems. The numerical results demonstrate that the APE combined with MLCBD is much more efficient than conventional MLCBD for analyzing the large-scale electromagnetic scattering problems.
机译:当使用表面积分方程方法解决电磁散射问题时,可以获得大型的密集复线性系统。为了有效地分析大型密集复杂线性系统,使用多级压缩块分解(MLCBD)来加速矩阵矢量乘法运算。尽管与直接矩量法相比,MLCBD效率高,但是对于大规模电磁问题,MLCBD的效率仍然较低。因此,本文提出了一种有效的MLCBD版本。它利用渐进相前提取(APE)来减少对计算机存储的过多依赖,并减少了MLCBD中用于分析大规模电磁问题的解决时间。数值结果表明,结合MPEBD的APE在分析大规模电磁散射问题方面比常规MLCBD更为有效。

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