Numerical solution methods for fractional partial differential equations

PhD Thesis


Osman, Sheelan Abdulkader. 2017. Numerical solution methods for fractional partial differential equations. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/5c075fc8baf89
Title

Numerical solution methods for fractional partial differential equations

TypePhD Thesis
Authors
AuthorOsman, Sheelan Abdulkader
SupervisorLanglands, Trevor
Stepanyants, Yury
Butler, Harry
Institution of OriginUniversity of Southern Queensland
Qualification NameDoctor of Philosophy
Number of Pages464
Year2017
Digital Object Identifier (DOI)https://doi.org/10.26192/5c075fc8baf89
Abstract

Fractional partial differential equations have been developed in many different fields such as physics, finance, fluid mechanics, viscoelasticity, engineering and biology. These models are used to describe anomalous diffusion. The main feature of these equations is their nonlocal property, due to the fractional derivative, which makes their solution challenging. However, analytic solutions of the fractional partial differential equations either do not exist or involve special functions, such as the Fox (H-function) function (Mathai & Saxena 1978) and the Mittag-Leffler function (Podlubny 1998) which are diffcult to evaluate. Consequently, numerical techniques are required to find the solution of fractional partial differential equations.

This thesis can be considered as two parts, the first part considers the approximation of the Riemann-Liouville fractional derivative and the second part develops numerical techniques for the solution of linear and nonlinear fractional partial differential equations where the fractional derivative is defied as a Riemann-Liouville derivative.

In the first part we modify the L1 scheme, developed initially by Oldham & Spanier (1974), to develop the three schemes which will be defined as the C1, C2 and C3 schemes. The accuracy of each method is considered. Then the memory effect of the fractional derivative due to nonlocal property is discussed. Methods of reduction of the computation L1 scheme are proposed using regression approximations.

In the second part of this study, we consider numerical solution schemes for linear fractional partial differential equations. Here the numerical approximation schemes are developed using an approximation of the fractional derivative and a spatial discretization scheme. In this thesis the L1, C1, C2, C3 fractional derivative approximation schemes, developed in the first part of the thesis, are used in conjunction with either the Centred-finite difference scheme, the Dufort-Frankel scheme or the Keller Box scheme. The stability of these numerical schemes are investigated via the technique of the Fourier analysis (Von Neumann stability analysis). The convergence of each the numerical schemes is also discussed. Numerical tests were used to conform the accuracy and stability of each proposed method.

In the last part of the thesis numerical schemes are developed to handle nonlinear partial differential equations and systems of nonlinear fractional partial differential equations. We considered two models of a reversible reaction in the presence of anomalous subdiffusion. The Centred-finite difference scheme and the Keller Box methods are used to spatially discretise the spatial domain in these schemes. Here the L1 scheme and a modification of the L1 scheme are used to approximate the fractional derivative. The accuracy of the methods are discussed and the convergence of the scheme are demonstrated by numerical experiments. We also give numerical examples to illustrate the e�ciency of the proposed scheme.

KeywordsRiemann-Liouville fractional derivative, Caputo fractional derivative, Grunwald-Letnikov fractional derivative, fractional subdiffusion equation, fractional advection-diffusion equation, accuracy, stability and convergence, L1 approximation, numerical method
ANZSRC Field of Research 2020490303. Numerical solution of differential and integral equations
Byline AffiliationsSchool of Agricultural, Computational and Environmental Sciences
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