A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution

This paper presents a fast Crank–Nicolson L1 finite difference scheme for the two-dimensional time fractional mobile/immobile diffusion equation with weakly singular solution at the initial moment. First, the time fractional derivative is discretized using the Crank–Nicolson formula on uniform meshes, and a local truncation error estimate is provided. The spatial derivative is discretized using the central difference quotient on uniform meshes. Then, energy analysis methods are utilized to provide an optimal error estimates. On the other hand, the numerical scheme is optimized based on the sum-of-exponentials approximation, effectively reducing computation and memory requirements. Finally, numerical examples are simulated to verify the effectiveness of the algorithm.

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Publication Details

Journal
Fractal and Fractional
Published
2025-03-26
DOI
https://doi.org/10.3390/fractalfract9040204
Citations
2
Primary Topic
Fractional Differential Equations Solutions
Type
article
Field-Weighted Citation Impact
2.74

Funders

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article

A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution

Aijie Cheng, Haili Qiao
2 citations
Fractal and Fractional
Fractional Differential Equations Solutions
2.74
article

A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution

Aijie Cheng, Haili Qiao
article en
2 citations

Abstract

This paper presents a fast Crank–Nicolson L1 finite difference scheme for the two-dimensional time fractional mobile/immobile diffusion equation with weakly singular solution at the initial moment. First, the time fractional derivative is discretized using the Crank–Nicolson formula on uniform meshes, and a local truncation error estimate is provided. The spatial derivative is discretized using the central difference quotient on uniform meshes. Then, energy analysis methods are utilized to provide an optimal error estimates. On the other hand, the numerical scheme is optimized based on the sum-of-exponentials approximation, effectively reducing computation and memory requirements. Finally, numerical examples are simulated to verify the effectiveness of the algorithm.

Fractal and FractionalVol. 9(4)
Shandong University (CN), Liaocheng University (CN)
Liaocheng University, Natural Science Foundation of Shandong Province
Openalex Percentile: Top 12%
Fractional Differential Equations Solutions
2.74
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A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution — Aijie Cheng, Haili Qiao · Fractal and Fractional (2025) | TGRS Research Map | TGRS