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arXiv 1608.01344math.NAcs.NA
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改进的迭代Crank-Nicolson方法与提高的精度

Modified Iterated Crank-Nicolson Method with Improved Accuracy

Delaware State University(特拉华州立大学)

Qiqi Tran, Jinjie Liu

AI总结:

本文提出两种改进的θ-ICN算法,通过不同方式选择权重θ,实现θ不为0.5时的二阶收敛性,通过稳定性分析和数值实验验证其准确性和稳定性。

摘要:

本文提出两种改进的θ-ICN算法,通过不同方式选择权重θ,实现θ不为0.5时的二阶收敛性,通过稳定性分析和数值实验验证其准确性和稳定性。

英文摘要:

The iterated Crank-Nicolson (ICN) method is a successful numerical algorithm in numerical relativity for solving partial differential equations. The $θ$-ICN method is the extension of the original ICN method where $θ$ is the weight when averaging the predicted and corrected values. It has better stability when $θ$ is chosen to be larger than 0.5, but the accuracy is reduced since the $θ$-ICN method is second order accurate only when $θ$ = 0.5. In this paper, we propose two modified $θ$-ICN algorithms that have second order of convergence rate when $θ$ is not 0.5, based on two different ways to choose the weight $θ$. The first approach employs two geometrically averaged $θ$s in two iterations within one time step, and the second one uses arithmetically averaged $θ$s for two consecutive time steps while $θ$ remains the same in each time step. The stability and second order accuracy of our methods are verified using stability and truncation error analysis and are demonstrated by numerical examples on linear and semi-linear hyperbolic partial differential equations and Burgers' equation.

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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