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Accuracy improved ADI-FDTD methods

机译:精度提高的ADI-FDTD方法

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摘要

FDTD method plays an important role for simulation of different structures in various fields of engineering, such as RF/microwaves, photonics and VLSI. However, due to the CFL stability constraint, the FDTD time step is still small and the related CPU time is still large for modelling fine geometry where small cell sizes are required to resolve fields. As a result, the unconditionally stable CFL-condition-free ADI-FDTD method is becoming a popular alternative to the FDTD method. The ADI-FDTD method allows the use of larger time steps; however, it comes at the cost of larger errors. To mitigate the problem of these larger errors, in this paper we propose to modify the conventional ADI-FDTD algorithm. The modifications are based on the fact that because the ADI-FDTD is a truncated form of the Crank-Nicolson (CN) method, the truncated terms can be re-introduced approximately into the ADI algorithms to improve accuracy. Two accuracy-improved ADI-FDTD algorithms are derived and then validated for two-dimensional cases. Unfortunately, in the three-dimensional case the proposed methods are not found to be unconditionally stable.
机译:FDTD方法在各种工程领域(例如RF /微波,光子学和VLSI)的不同结构的仿真中起着重要作用。但是,由于CFL稳定性约束,FDTD时间步长仍然很小,并且相关的CPU时间对于建模精细几何体(其中需要较小的像元大小才能解析字段)的建模仍然很大。结果,无条件稳定的无CFL无条件ADI-FDTD方法正成为FDTD方法的流行替代方法。 ADI-FDTD方法允许使用更大的时间步长;但是,这是以更大的错误为代价的。为了减轻这些较大误差的问题,我们建议对常规ADI-FDTD算法进行修改。修改基于以下事实:由于ADI-FDTD是Crank-Nicolson(CN)方法的截断形式,因此可以将截断项近似重新引入ADI算法以提高准确性。推导了两种精度提高的ADI-FDTD算法,然后针对二维情况进行了验证。不幸的是,在三维情况下,并未发现所提出的方法是无条件稳定的。

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