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首页> 外文期刊>International journal of applied electromagnetics and mechanics >Fast analysis of large-scale problems by modified multilevel compressed block decomposition combined with high order hierarchical basis functions
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Fast analysis of large-scale problems by modified multilevel compressed block decomposition combined with high order hierarchical basis functions

机译:通过修改的多级压缩块分解进行大规模问题的快速分析,与高阶分层基础函数相结合

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摘要

For the electrically large problems, the discrete unknowns of surface integral equation are very large, resulting in the matrix condition is relatively poor. The high order hierarchical basis functions are utilized to reduce the discrete unknowns, thereby reducing the memory consumption and computation time. Meanwhile, modified multilevel compressed block decomposition (MMLCBD) is applied to accelerate the matrix-vector multiplication operations, which utilizes novel technique to improve the solving efficiency by combining a less accurate truncating threshold in MLCBD with a rapid and cheap iterative refinement process. Combining the high order hierarchical basis functions with MMLCBD can make good use of their respective advantages to analyze the large-scale electromagnetic problems efficiently. The numerical results demonstrate that the proposed method is much more efficient than conventional MLCBD for analyzing the large-scale electromagnetic problems.
机译:对于电力的问题,表面积分方程的离散未知是非常大的,导致矩阵条件相对较差。 高阶分层基本函数用于减少离散未知数,从而降低存储器消耗和计算时间。 同时,应用修改的多级压缩块分解(MMLCBD)来加速矩阵矢量乘法操作,该乘法传染措施利用新技术通过组合具有快速和廉价的迭代细化过程的MLCBD中的不太精确截断阈值来提高解决效率。 将高阶层次函数与MMLCBD相结合,可以良好地利用各自的优势来有效地分析大规模电磁问题。 数值结果表明,所提出的方法比传统的MLCBD更有效,用于分析大规模的电磁问题。

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