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arXiv 1503.05166math.NAcs.NA
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时间步进中的全局误差估计

Estimating Global Errors in Time Stepping

Argonne National Laboratory(阿贡国家实验室)

Emil Constantinescu

AI总结:

本文提出新的时间步进策略,内置全局误差估计器,通过传播缺陷类似求解修正或Zadunaisky过程,实现更通用的微分方程数值解法。

摘要:

本研究引入了新的时间步进策略,内置全局误差估计器。新方法在数值解中传播缺陷,类似于求解修正或Zadunaisky过程;然而,所提方法允许内部计算重叠,因此代表了经典数值方案在具有全局误差估计的微分方程求解中的泛化。所得算法可有效表示为通用线性方法。我们提出了几种类似于Runge-Kutta方法的显式自启动方案,并在多个示例上阐述了理论考虑。

英文摘要:

This study introduces new time-stepping strategies with built-in global error estimators. The new methods propagate the defect along with the numerical solution much like solving for the correction or Zadunaisky's procedure; however, the proposed approach allows for overlapped internal computations and, therefore, represents a generalization of the classical numerical schemes for solving differential equations with global error estimation. The resulting algorithms can be effectively represented as general linear methods. We present a few explicit self-starting schemes akin to Runge-Kutta methods with global error estimation and illustrate the theoretical considerations on several examples.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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