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Incomplete-Leaf Multilevel Fast Multipole Algorithm for Multiscale Penetrable Objects Formulated With Volume Integral Equations

机译:基于体积积分方程的多尺度可穿透物体的不完整叶多级快速多极算法

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摘要

Recently introduced incomplete-leaf (IL) tree structures for multilevel fast multipole algorithm (referred to as IL-MLFMA) is proposed for the analysis of multiscale inhomogeneous penetrable objects, in which there are multiple orders of magnitude differences among the mesh sizes. Considering a maximum Schaubert-Wilton-Glisson function population threshold per box, only overcrowded boxes are recursively divided into proper smaller boxes, leading to IL tree structures consisting of variable box sizes. Such an approach: 1) significantly reduces the CPU time for near-field calculations regarding overcrowded boxes, resulting a superior efficiency in comparison with the conventional MLFMA where fixed-size boxes are used and 2) effectively reduces the computational error of the conventional MLFMA for multiscale problems, where the protrusion of the basis/testing functions from their respective boxes dramatically impairs the validity of the addition theorem. Moreover, because IL-MLFMA is able to use deep levels safely and without compromising the accuracy, the memory consumption is significantly reduced compared with that of the conventional MLFMA. Several examples are provided to assess the accuracy and the efficiency of IL-MLFMA for multiscale penetrable objects.
机译:提出了最近引入的用于多级快速多极算法的不完整叶(IL)树结构(称为IL-MLFMA)来分析多尺度不均匀可穿透对象,其中网格大小之间存在多个数量级的差异。考虑到每个框的最大Schaubert-Wilton-Glisson函数人口阈值,仅将拥挤的框递归地划分为适当的较小框,从而导致由可变框大小组成的IL树结构。这种方法:1)大大减少了关于拥挤的盒子的近场计算所需的CPU时间,与使用固定尺寸盒子的常规MLFMA相比,效率更高; 2)有效地减少了传统MLFMA用于计算的错误。多尺度问题,其中基础/测试函数从各自的方框中突出会极大地损害加法定理的有效性。此外,由于IL-MLFMA能够安全地使用深度级别,而不会影响精度,因此与传统的MLFMA相比,显着减少了内存消耗。提供了几个示例来评估IL-MLFMA对多尺度可穿透物体的准确性和效率。

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