A fast fractional block-centered finite difference method for two-sided space-fractional diffusion equations on general nonuniform grids

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-10-18 DOI:10.1007/s13540-024-00346-5
Meijie Kong, Hongfei Fu
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Abstract

In this paper, a two-sided variable-coefficient space-fractional diffusion equation with fractional Neumann boundary condition is considered. To conquer the weak singularity caused by nonlocal space-fractional differential operators, a fractional block-centered finite difference (BCFD) method on general nonuniform grids is proposed. However, this discretization still results in an unstructured dense coefficient matrix with huge memory requirement and computational complexity. To address this issue, a fast version fractional BCFD algorithm by employing the well-known sum-of-exponentials (SOE) approximation technique is also proposed. Based upon the Krylov subspace iterative methods, fast matrix-vector multiplications of the resulting coefficient matrices with any vector are developed, in which they can be implemented in only \({\mathcal {O}}(MN_{exp})\) operations per iteration without losing any accuracy compared to the direct solvers, where \(N_{exp}\ll M\) is the number of exponentials in the SOE approximation. Moreover, the coefficient matrices do not necessarily need to be generated explicitly, while they can be stored in \({\mathcal {O}}(MN_{exp})\) memory by only storing some coefficient vectors. Numerical experiments are provided to demonstrate the efficiency and accuracy of the method.

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一般非均匀网格上双面空间分数扩散方程的快速分数块中心有限差分法
本文考虑了一个具有分数 Neumann 边界条件的两边可变系数空间分数扩散方程。为了克服非局部空间分数微分算子引起的弱奇异性,本文提出了一种在一般非均匀网格上的分数块中心有限差分(BCFD)方法。然而,这种离散化方法仍然会产生一个非结构化的密集系数矩阵,带来巨大的内存需求和计算复杂性。为解决这一问题,研究人员还提出了一种快速分数 BCFD 算法,该算法采用了著名的指数和(SOE)近似技术。基于 Krylov 子空间迭代法,开发出了任意矢量的系数矩阵的快速矩阵-矢量乘法,与直接求解器相比,每次迭代只需 \({\mathcal {O}}(MN_{exp})\) 次运算即可实现,且不会损失任何精度,其中 \(N_{exp}\ll M\) 是 SOE 近似中指数的个数。此外,系数矩阵并不一定需要明确生成,而只需存储一些系数向量,就可以将它们存储在内存中({mathcal {O}}(MN_{exp})\) 。数值实验证明了该方法的高效性和准确性。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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