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Convolutional perfectly matched layer (CPML) for fundamental LOD-FDTD method with 2nd order temporal accuracy and complying divergence

机译:基本LOD-FDTD方法的卷积完美匹配层(CPML),具有2 阶时间精度和顺应散度

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This paper extends the unconditionally stable locally one-dimensional finite-difference time-domain method with second-order temporal accuracy and complying divergence (denoted as LOD2-CD-FDTD) by incorporating the convolutional perfectly matched layer (CPML). To further enhance efficiency, the LOD2-CD-FDTD method with CPML is formulated into the fundamental form with the simplest and most concise right-hand sides free of matrix operators. The explicit output processing of the LOD2-CD-FDTD method has complying divergence, and it is also independent of the CPML media. Numerical results are presented to validate the formulation.
机译:本文通过结合卷积完全匹配层(CPML),扩展了具有二阶时间精度和顺应性发散的无条件稳定局部一维有限差分时域方法(称为LOD2-CD-FDTD)。为了进一步提高效率,采用CPML的LOD2-CD-FDTD方法被公式化为基本形式,最简单,最简洁的右侧没有矩阵运算符。 LOD2-CD-FDTD方法的显式输出处理具有一致的差异,并且它也独立于CPML介质。数值结果表明了该配方的有效性。

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