Abstract
Radial basis function-based finite difference (RBF-FD) schemes generalize finite difference methods, providing flexibility in node distribution as well as the shape of the domain. In this paper, we consider a numerical formulation based on RBF-FD for solving a time–space fractional diffusion problem defined using a fractional Laplacian operator. The model problem is simplified into a local problem in space using the Caffarelli–Silvestre extension method. The space derivatives in the resulting problem are then discretized using a local RBF-based finite difference method, while L1 approximation is used for the fractional time derivative. Results obtained using the proposed scheme are then compared with that given in the existing literature.
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References
Pozrikidis C (2018) The fractional Laplacian. CRC Press, Boca Raton
Zhu T, Harris JM (2014) Modeling acoustic wave propagation in heterogeneous attenuating media using decoupled fractional Laplacians. Geophysics 79:T105–T116
Kwaśnicki M (2017) Ten equivalent definitions of the fractional Laplace operator. Fract Calc Appl Anal 20:7–51
Lischke A, Pang G, Gulian M, Song F, Glusa C, Zheng X, Mao Z, Cai W, Meerschaert MM, Ainsworth M, Karniadakis GE (2019) What is the fractional Laplacian? A comparative review with new results. J Comput Phys 404:109009
Hu Y, Li C, Li H (2017) The finite difference method for Caputo-type parabolic equation with fractional Laplacian: one-dimension case. Chaos Solitons Fractals 102:319–326
Sheng C, Shen J, Tang T, Wang LL, Yuan H (2020) Fast Fourier-like mapped Chebyshev spectral–Galerkin methods for PDEs with integral fractional Laplacian in unbounded domains. SIAM J Numer Anal 58:2435–2464
Bonito A, Borthagaray JP, Nochetto RH, Otárola E, Salgado AJ (2018) Numerical methods for fractional diffusion. Comput Vis Sci 19:19–46
Ainsworth M, Glusa C (2018) Hybrid finite element-spectral method for the fractional Laplacian: approximation theory and efficient solver. SIAM J Sci Comput 40:A2383–A2405
Yuan H (2021) An efficient spectral–Galerkin method for fractional reaction-diffusion equations in unbounded domains. J Comput Phys 428:1–17
Fornberg B, Flyer N (2015) A Primer on Radial Basis Functions with Applications to the Geosciences, Society for Industrial and Applied Mathematics
Zhang Y (2019) An accurate and stable RBF method for solving partial differential equations. Appl Math Lett 97:93–98
Chen W, Ye L, Sun H (2010) Fractional diffusion equations by the Kansa method. Comput Math Appl 59:1614–1620
Piret C, Hanert E (2013) A radial basis functions method for fractional diffusion equations. J Comput Phys 238:71–81
Pang G, Chen W, Fu Z (2015) Space-fractional advection-dispersion equations by the Kansa method. J Comput Phys 293:280–296
Wright GB, Fornberg B (2006) Scattered node compact finite difference-type formulas generated from radial basis functions. J Comput Phys 212:99–123
Caffarelli L, Silvestre L (2007) An extension problem related to the fractional Laplacian. Commun Part Differ Equ 32:1245–1260
Capella A, Dávila J, Dupaigne L, Sire Y (2011) Regularity of radial extremal solutions for some non-local semilinear equations. Commun Part Differ Equ 36:1353–1384
Hu Y, Li C, Li H (2018) The finite difference method for Caputo-type parabolic equation with fractional Laplacian: more than one space dimension. Int J Comput Math 95:1114–1130
Hu Y, Cheng F (2020) The finite element method for fractional diffusion with spectral fractional Laplacian. Math Methods Appl Sci 43:1–17
Kumar P, Erturk V.S, Murillo M, Harley C (2022) Generalized forms of fractional Euler and Runge–Kutta methods using non-uniform grid, Int J Nonlinear Sci Numer Simul
Marasi HR, Derakhshan MH, Joujehi AS, Kumar P (2023) Higher-order fractional linear multi-step methods. Phys Scr 98:024004
Li C, Cai M (2019) Theory and Numerical Approximations of Fractional Integrals and Derivatives, Society for Industrial and Applied Mathematics
Oldham K, Spanier J (1974) The fractional calculus theory and applications of differentiation and integration to arbitrary order, 1st edn. Academic Press, New York, vol 2
Kumar P, Erturk VS, Murillo M, Venkatesan G (2023) A new form of L1-Predictor-Corrector scheme to solve multiple delay-type fractional order systems with the example of a neural network model. Fractals 13:2340043
Acknowledgements
The first author acknowledges CSIR, India, for the financial support through CSIR-JRF/SRF fellowship.
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The research of the corresponding author (Revathy) is supported by the Council of Scientific & Industrial Research (CSIR), India under Grant Number: 09/886(0001)/2019-EMR-I.
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JMR: Literature survey, implementation, manuscript preparation. GC: Ideation, supervision, manuscript editing.
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Revathy, J.M., Chandhini, G. Solution of space–time fractional diffusion equation involving fractional Laplacian with a local radial basis function approximation. Int. J. Dynam. Control 12, 237–245 (2024). https://doi.org/10.1007/s40435-023-01237-y
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DOI: https://doi.org/10.1007/s40435-023-01237-y