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Research Article | Open Access

Chebyshev fifth-kind series approximation for generalized space fractional partial differential equations

Khalid K. Ali1( )Mohamed A. Abd El Salam1Mohamed S. Mohamed2
Department of Mathematics, Faculty of Science, Al Azhar University, Nasr City 11884, Cairo, Egypt
Department of Mathematics, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
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Abstract

In this paper, we propose a numerical scheme to solve generalized space fractional partial differential equations (GFPDEs). The proposed scheme uses Shifted Chebyshev fifth-kind polynomials with the spectral collocation approach. Besides, the proposed GFPDEs represent a great generalization of significant types of fractional partial differential equations (FPDEs) and their applications, which contain many previous reports as a special case. The fractional differential derivatives are expressed in terms of the Caputo sense. Moreover, the Chebyshev collocation method together with the finite difference method is used to reduce these types of differential equations to a system of differential equations which can be solved numerically. In addition, the classical fourth-order Runge-Kutta method is also used to treat the differential system with the collocation method which obtains a great accuracy. Numerical approximations performed by the proposed method are presented and compared with the results obtained by other numerical methods. The introduced numerical experiments are fractional-order mathematical physics models, as advection-dispersion equation (FADE) and diffusion equation (FDE). The results reveal that our method is a simple, easy to implement and effective numerical method.

CLC number: 65N35, 35G05

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AIMS Mathematics
Pages 7759-7780

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Cite this article:
Ali KK, Abd El Salam MA, Mohamed MS. Chebyshev fifth-kind series approximation for generalized space fractional partial differential equations. AIMS Mathematics, 2022, 7(5): 7759-7780. https://doi.org/10.3934/math.2022436

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Received: 15 December 2021
Revised: 15 December 2021
Accepted: 09 February 2022
Published: 15 May 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)