An iterated, multipoint differential transform method for numerically evolving partial differential equation initial-value problems

H. Finkel
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引用次数: 2

Abstract

Traditional numerical techniques for solving time-dependent partial differential equation (PDE) initial-value problems (IVPs) store a truncated representation of the function values and a certain number of their time derivatives at each time step. Although redundant in the dx → 0 limit, what if spatial derivatives were also stored? This paper presents an iterated, multipoint differential transform method (IMDTM) for numerically evolving PDE IVPs. Using this scheme, we demonstrate that stored spatial derivatives can be propagated in an efficient and self-consistent manner and can effectively contribute to the evolution procedure in a way that can confer several advantages, including aiding in solution verification. Lastly, in order to efficiently implement the IMDTM scheme, a generalized finite-difference stencil formula is derived that can take advantage of multiple higher-order spatial derivatives when computing even-higher-order derivatives. As demonstrated here, the performance of these techniques compares favorably to other explicit evolution schemes in terms of speed, memory footprint and accuracy.
数值演化偏微分方程初值问题的迭代多点微分变换方法
求解时变偏微分方程(PDE)初值问题的传统数值方法在每个时间步长存储函数值的截断表示及其一定数量的时间导数。虽然在dx→0极限下是冗余的,但如果空间导数也被存储了呢?本文提出了一种迭代多点微分变换方法(IMDTM),用于数值演化的PDE ivp。使用该方案,我们证明了存储的空间导数可以以高效和自一致的方式传播,并且可以有效地为进化过程做出贡献,这种方式可以赋予一些优势,包括帮助解决方案验证。最后,为了有效地实现IMDTM方案,推导了一个广义有限差分模板公式,该公式在计算偶高阶导数时可以利用多个高阶空间导数。如本文所示,这些技术的性能在速度、内存占用和准确性方面优于其他显式演化方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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