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 meshe...

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Main Authors: Haili Qiao, Aijie Cheng
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Fractal and Fractional
Subjects:
Online Access:https://www.mdpi.com/2504-3110/9/4/204
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author Haili Qiao
Aijie Cheng
author_facet Haili Qiao
Aijie Cheng
author_sort Haili Qiao
collection DOAJ
description 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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publishDate 2025-03-01
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series Fractal and Fractional
spelling doaj-art-3da741be83894ef391ba65a73ccd498c2025-08-20T02:28:28ZengMDPI AGFractal and Fractional2504-31102025-03-019420410.3390/fractalfract9040204A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular SolutionHaili Qiao0Aijie Cheng1School of Mathematical Sciences, Liaocheng University, Liaocheng 252059, ChinaSchool of Mathematics, Shandong University, Jinan 250100, ChinaThis 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.https://www.mdpi.com/2504-3110/9/4/2042D time fractional mobile/immobile equationweak singularityCrank–Nicolson L1 formulaerror estimatessum-of-exponentials approximation
spellingShingle Haili Qiao
Aijie Cheng
A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution
Fractal and Fractional
2D time fractional mobile/immobile equation
weak singularity
Crank–Nicolson L1 formula
error estimates
sum-of-exponentials approximation
title A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution
title_full A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution
title_fullStr A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution
title_full_unstemmed A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution
title_short A Fast Finite Difference Method for 2D Time Fractional Mobile/Immobile Equation with Weakly Singular Solution
title_sort fast finite difference method for 2d time fractional mobile immobile equation with weakly singular solution
topic 2D time fractional mobile/immobile equation
weak singularity
Crank–Nicolson L1 formula
error estimates
sum-of-exponentials approximation
url https://www.mdpi.com/2504-3110/9/4/204
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