Hybrid technique for multi-dimensional fractional diffusion problems involving Caputo-Fabrizio derivative

被引:1
|
作者
Yadav, Surendar Kumar [1 ]
Purohit, Mridula [1 ]
Gour, Murli Manohar [1 ]
Yadav, Lokesh Kumar [1 ]
Mishra, Manvendra Narayan [2 ]
机构
[1] Vivekananda Global Univ Jaipur, Dept Math, Jaipur, Rajasthan, India
[2] Suresh Gyan Vihar Univ, Dept Math, Jaipur, Rajasthan, India
来源
INTERNATIONAL JOURNAL OF MATHEMATICS FOR INDUSTRY | 2024年
关键词
Multi-dimensional fractional diffusion problems; Adomain polynomials; Shehu transform; non-singular fractional derivative; EQUATION; LAPLACE; MODEL;
D O I
10.1142/S2661335224500205
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this study, a precise and analytical method, namely Shehu transform decomposition method (STDM), is applied to examine multi-dimensional fractional diffusion equations, which will describe density dynamics in a material undergoing diffusion. The fractional derivative is taken into account by the Caputo-Fabrizio (CF) derivative. The proposed approach combines the Shehu transformation (ST) with the Adomian decomposition method (ADM), employing Adomain polynomials to handle nonlinear terms. Fixed point theorem has been used to prove the uniqueness and existence of the solution of governing differential equation. To validate the accuracy of proposed method, we present the analytical solutions of three applications of multi-dimensional fractional diffusion equations. Furthermore, we compute the graphical and numerical results using MATLAB to demonstrate the close-form analytical solution in the comparison of the exact solution. The obtained findings are promising and suitable for the solution of multi-dimensional diffusion problems with time-fractional derivatives. The main advantage is that our developed scheme does not require assumptions or restrictions on variables that ruin the actual problem. This scheme plays a significant role in finding the solution and overcoming the restriction of variables that may cause difficulty in modeling the problem.
引用
收藏
页数:10
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